Population Estimates Research Articles

The Population of Massive Stars in Active Galactic Nuclei Disks

Gravitational instability in the outskirts of active galactic nuclei (AGN) disks leads to disk fragmentation and formation of ∼300 M ⊙ supermassive stars with potentially long lifetimes. Alternatively, stars can be captured ex situ and grow from gas accretion in the AGN disk. However, the number density distribution throughout the disk is limited by thermal feedback as their luminosities provide the dominant heating source. We derive equilibrium stellar surface density profiles under two limiting contexts: in the case where the stellar lifetimes are prolonged, due to the recycling of hydrogen-rich disk gas, only the fraction of gas converted into heat is removed from the disk accretion flow. Alternatively, if stellar composition recycling is inefficient and stars can evolve off the main sequence, the disk accretion rate is quenched toward smaller radii resembling a classical starburst disk, albeit the effective removal rate depends not only on the stellar lifetime, but also the mass of stellar remnants. For AGNs with central supermassive black hole masses of ∼106–108 M ⊙ accreting at ∼0.1 Eddington efficiency, we estimate a total number of 103–105 massive stars and the rate of stellar mergers to be 10−3 to 1 yr−1. We initiate the detailed study of the interaction between a swarm of massive stars through hydro and N-body simulations to provide better prescriptions of dynamical processes in AGN disks, and to constrain more accurate estimates of the stellar population.

Underreporting or Failed Notification? Global Botulism Reporting, 2000-2022.

Botulism is a rare, potentially fatal illness caused by botulinum toxins produced by Clostridium bacteria. There are no coordinated worldwide reporting mechanisms for botulism cases and therefore few reliable case frequency estimates. This study aimed to establish an international benchmark for case frequency to determine estimated global rates of underreporting of botulism cases. To this end, a comprehensive, multilingual search of major global and national databases, including gray data and government sources, was performed. Data from case series were pooled, standardized against United Nations midyear population estimates, and analyzed using Kolmogorov-Smirnov tests to identify normally distributed data series. National incidence rates of normally distributed series were compared with that of the United States, which was considered the gold standard due to its extensive data reported for 2004-2018. A total of 6,932 botulism cases from 59 nations were identified in the literature, with a global case fatality rate of 1.37%. The national mean incidence rate ranged from 0.00 to 8.04 cases per million people, with an international mean incidence rate of 0.62 cases per million people. At the continent level, incidence rates tended toward normal distributions, although few countries outside of North America and Europe exhibited normal distributions. Based on comparisons with the US standard, an estimated 88.71% of botulism cases worldwide were unreported in 2016. Better awareness of botulism among healthcare professionals, coordinated global reporting mechanisms, and research on additional contributing factors to underreporting would enable better understanding of global case frequency, thereby potentially reducing the global incidence of botulism and improving outcomes.

Even low levels of cannibalism can bias population estimates for Pacific hake

Abstract By incorporating trophic interactions and temperature-dependent bioenergetics, multi-species models such as CEATTLE (climate-enhanced age-based model with temperature-specific trophic linkages and energetics) are a step towards ecosystem-based stock assessment and management of high-value commercial species such as Pacific hake (Merluccius productus). Hake are generalist predators and previous studies in the California Current Ecosystem have determined that their diet consists of ∼30% cannibalism. We used CEATTLE to include cannibalism in a model of hake population dynamics and re-examined hake diet data to determine the proportion by age that can attributed to cannibalism. The proportion was highly variable, ranging between 0 and 80% of stomach contents by weight. When included in the CEATTLE model, the estimated spawning biomass, total biomass, and recruitment increased by 15, 23, and 58%, on average, relative to the single-species model, due to the estimation of time- and age-varying predation mortality, primarily for age-1 hake. The effects of cannibalism varied over time, with further increases in total biomass and recruitment resulting from the age structure of the population following large cohorts in 1980 and 1984. Results from the cannibalism model could be used to inform the estimation of time- and age-varying mortality in the single-species assessment and as a pathway for including ecosystem information in management through environmental and trophic drivers of variability in mortality.

Deconvolution analysis identified altered hepatic cell landscape in primary sclerosing cholangitis and primary biliary cholangitis.

Primary sclerosing cholangitis (PSC) and primary biliary cholangitis (PBC) are characterized by ductular reaction, hepatic inflammation, and liver fibrosis. Hepatic cells are heterogeneous, and functional roles of different hepatic cell phenotypes are still not defined in the pathophysiology of cholangiopathies. Cell deconvolution analysis estimates cell fractions of different cell phenotypes in bulk transcriptome data, and CIBERSORTx is a powerful deconvolution method to estimate cell composition in microarray data. CIBERSORTx performs estimation based on the reference file, which is referred to as signature matrix, and allows users to create custom signature matrix to identify specific phenotypes. In the current study, we created two custom signature matrices using two single cell RNA sequencing data of hepatic cells and performed deconvolution for bulk microarray data of liver tissues including PSC and PBC patients. Custom signature matrix files were created using single-cell RNA sequencing data downloaded from GSE185477 and GSE115469. Custom signature matrices were validated for their deconvolution performance using validation data sets. Cell composition of each hepatic cell phenotype in the liver, which was identified in custom signature matrices, was calculated by CIBERSORTx and bulk RNA sequencing data of GSE159676. Deconvolution results were validated by analyzing marker expression for the cell phenotype in GSE159676 data. CIBERSORTx and custom signature matrices showed comprehensive performance in estimation of population of various hepatic cell phenotypes. We identified increased population of large cholangiocytes in PSC and PBC livers, which is in agreement with previous studies referred to as ductular reaction, supporting the effectiveness and reliability of deconvolution analysis in this study. Interestingly, we identified decreased population of small cholangiocytes, periportal hepatocytes, and interzonal hepatocytes in PSC and PBC liver tissues compared to healthy livers. Although further studies are required to elucidate the roles of these hepatic cell phenotypes in cholestatic liver injury, our approach provides important implications that cell functions may differ depending on phenotypes, even in the same cell type during liver injury. Deconvolution analysis using CIBERSORTx could provide a novel approach for studies of specific hepatic cell phenotypes in liver diseases.

Supplemental structured surveys and pre-existing detection models improve fine-scale density and population estimation with opportunistic community science data

Density and population estimates aid in conservation and stakeholder communication. While free and broadly available community science data can effectively inform species distribution models, they often lack the information necessary to estimate imperfect detection and area sampled, thus limiting their use in fine-scale density modeling. We used structured distance-sampling surveys to model detection probability and calculate survey-specific detection offsets in community science models. We estimated density and population for 16 songbird species under three frameworks: (1) a fixed framework that assumes perfect detection within a specified survey radius, (2) an independent framework that calculates offsets from an independent source, and (3) a calibration framework that calculates offsets from supplemental surveys. Within the calibration framework, we examined the effects of calibration dataset size and data pooling. Estimates of density and population size were consistently biased low in the fixed framework. The independent and calibration frameworks produced reliable estimates for some species, but biased estimates for others, indicating discrepancies in detection probability between structured and community science surveys. The calibration framework produced reliable population estimates with as few as 10 calibration surveys with positive detections. Data pooling dramatically decreased bias. This study provides conservationists and managers with a cost-effective method of estimating density and population.

Randomness and retention: using weak mean motion resonances to constrain Neptune’s late-stage migration

ABSTRACT Planet–planetesimal interactions cause a planet to migrate, manifesting as a random walk in semimajor axis. In models for Neptune’s migration involving a gravitational upheaval, this planetesimal-driven migration is a side-effect of the dynamical friction required to damp Neptune’s orbital eccentricity. This migration is noisy, potentially causing Trans-Neptunian Objects (TNOs) in mean motion resonance to be lost. With N-body simulations, we validate a previously derived analytic model for resonance retention and determine unknown coefficients. We identify the impact of random-walk (noisy) migration on resonance retention for resonances up to fourth order lying between 39 and 75 au. Using a population estimate for the weak 7:3 resonance from the well-characterized Outer Solar System Origins Survey (OSSOS), we rule out two cases: (1) a planetesimal disc distributed between 13.3 and 39.9 au with ≳ 30 Earth masses in today’s size distribution and Tmig ≳ 40 Myr and (2) a top-heavy size distribution with ≳2000 Pluto-sized TNOs and Tmig ≳10 Myr, where Tmig is Neptune’s migration time-scale. We find that low-eccentricity TNOs in the heavily populated 5:2 resonance are easily lost due to noisy migration. Improved observations of the low-eccentricity region of the 5:2 resonance and of weak mean motion resonances with Rubin Observatory’s Legacy Survey of Space and Time will provide better population estimates, allowing for comparison with our model’s retention fractions and providing strong evidence for or against Neptune’s random interactions with planetesimals.

Sometimes simple is good enough: An analysis of methods for residential building population estimation

AbstractResidential building population data can be useful in a breadth of urban planning, health, transportation, and business applications. Unfortunately, complete datasets of residential building populations are not widely available for use in Canada, and therefore either larger census geographies are used or residential building populations must be estimated. This research explores four different methods of estimating residential building populations, including: an equal allocation method, two measures based on building volume, and a novel method that integrates census data at the dissemination area level to calibrate a population estimation model. This work comprises three parts: 1) a description of these approaches, 2) an evaluation of their validity in a case study in Hamilton, Ontario, and 3) an application of these methods in measuring spatial accessibility to schools. Our results show that most methods yield very similar results, and most provide reasonable estimates of building populations that could be useful for some analytical tasks. However, all methods resulted in instances of error, particularly for the largest population buildings. We conclude that while more complex methods do not significantly outperform simpler methods based on building volume alone, the blend of these methods could yield more accurate population predictions.

Global food security estimation: Refining the IFSA caloric threshold using population estimates and projections by age and sex

Global food security estimation: Refining the IFSA caloric threshold using population estimates and projections by age and sex

An integrated population model and sensitivity assessment for a data-poor population of green sturgeon

Conservation planning requires understanding population sizes and trajectories. As with many imperiled species, green sturgeon ( Acipenser medirostris) census data are limited, making it difficult to contextualize current threats and promote quantitative conservation goals. We combined spawning census, growth, and demographic data for the southern population of green sturgeon to build a population size and trajectory estimate. We generated a distribution of population size estimates and trajectories reflecting uncertainty from multiple sources. We then propagate these estimates through a demographic model to assess the potential impact of fishing bycatch. Our model suggests the population is below the recovery goal of 3000 adults. The most probable current total population estimate (including juveniles) is approximately 10 000 fish (5300–18 400 95% high density interval (HDI)), with 2400 adults (2197–2624 95% HDI). Simulated fishing bycatch pressure on the adults and subadults reduced abundance by a median value of 0.4% per year, which could be an impediment to recovery. Fisheries bycatch is one of many threats this population faces; this integrated framework may be used to assess how other threats may affect this population.

A Multi-scale features-based cloud detection method for Suomi-NPP VIIRS day and night imagery

Abstract. Cloud detection is a necessary step before the application of remote sensing images. However, most methods focus on cloud detection in daytime remote sensing images. The ignored nighttime remote sensing images play more and more important role in many fields such as urban monitoring, population estimation and disaster assessment. The radiation intensity similarity between artificial lights and clouds is higher in nighttime remote sensing images than in daytime remote sensing images, which makes it difficult to distinguish artificial lights from clouds. Therefore, this paper proposes a deep learning-based method (MFFCD-Net) to detect clouds for day and nighttime remote sensing images. MFFCD-Net is designed based on the encoder-decoder structure. The encoder adopts Resnet-50 as the backbone network for better feature extraction, and a dilated residual up-sampling module (DR-UP) is designed in the decoder for up-sampling feature maps while enlarging the receptive field. A multi-scale feature extraction fusion module (MFEF) is designed to enhance the ability of the MFFCD-Net to distinguish regular textures of artificial lights and random textures of clouds. An Global Feature Recovery Fusion Module (GFRF Module) is designed to select and fuse the feature in the encoding stage and the feature in the decoding stage, thus to achieve better cloud detection accuracy. This is the first time that a deep learning-based method is designed for cloud detection both in day and nighttime remote sensing images. The experimental results on Suomi-NPP VIIRS DNB images show that MFFCD-Net achieves higher accuracy than baseline methods both in day and nighttime remote sensing images. Results on daytime remote sensing images indicate that MFFCD-Net can obtain better balance on commission and omission rates than baseline methods (92.3% versus 90.5% on F1-score). Although artificial lights introduced strong interference in cloud detection in nighttime remote sensing images, the accuracy values of MFFCD-Net on OA, Precision, Recall, and F1-score are still higher than 90%. This demonstrates that MFFCD-Net can better distinguish artificial lights from clouds than baseline methods in nighttime remote sensing images. The effectiveness of MFFCD-Net proves that it is very promising for cloud detection both in day and nighttime remote sensing images.

Identifying potentially low value surgical care: A national ecological study in England.

High variation in clinical practice may indicate uncertainty and potentially low-value care. Methods to identify low value care are often not well defined or transparent and can be time intensive. In this paper we explore the usefulness of variation analysis of routinely-collected data about surgical procedures in England to identify potentially low-value surgical care. This is a national ecological study using Hospital Episode Statistics linked to mid-year population estimates and indices of multiple deprivation in England, 2014/15-2018/19. We identified the top 5% of surgical procedures in terms of growth in standardised procedure rates for 2014/15 to 2018/19 and variation in procedure rates between clinical commissioning groups as measured by the systematic component of variance (SCV). A targeted literature review was conducted to explore the evidence for each of the identified techniques. Procedures without evidence of cost-effectiveness were viewed as of potentially low value. We identified six surgical procedures that had a high growth rate of 37% or more over 5years, and four with higher geographical variation (SCV >1.6). There was evidence for two of the 10 procedures that surgery was more cost-effective than non-surgical treatment albeit with uncertainty around optimal surgical technique. The evidence base for eight procedures was less clear cut, with uncertainty around clinical- and/or cost-effectiveness. These were: deep brain stimulation; removing the prostate; surgical spine procedures; a procedure to alleviate pain in the spine; surgery for dislocated joints due to trauma and associated surgery for traumatic fractures; hip joint replacement with cemented pelvic component or cemented femoral component; and shoulder joint replacement. This study demonstrates that variation analysis could be regularly used to identify potentially low-value procedures. This can provide important insights into optimising services and the potential de-adoption of costly interventions and treatments that do not benefit patients and the health system more widely. Early identification of potentially low value care can inform prioritisation of clinical trials to generate evidence on effectiveness and cost-effectiveness before treatments become established in clinical practice.

Self-Administration of Aspirin After Chest Pain for the Prevention of Premature Cardiovascular Mortality in the United States: A Population-Based Analysis.

Aspirin, an effective, low-cost pharmaceutical, can significantly reduce mortality if used promptly after acute myocardial infarction (AMI). However, many AMI survivors do not receive aspirin within a few hours of symptom onset. Our aim was to quantify the mortality benefit of self-administering aspirin at chest pain onset, considering the increased risk of bleeding and costs associated with widespread use. We developed a population simulation model to determine the impact of self-administering 325 mg aspirin within 4 hours of severe chest pain onset. We created a synthetic cohort of adults ≥ 40 years old experiencing severe chest pain using 2019 US population estimates, AMI incidence, and sensitivity/specificity of chest pain for AMI. The number of annual deaths delayed was estimated using evidence from a large, randomized trial. We also estimated the years of life saved (YOLS), costs, and cost per YOLS. Initiating aspirin within 4 hours of severe chest pain onset delayed 13 016 (95% CI, 11 643-14 574) deaths annually, after accounting for deaths due to bleeding (963; 926-1003). This translated to an estimated 166 309 YOLS (149391-185 505) at the cost of $643 235 (633 944-653 010) per year, leading to a cost-effectiveness ratio of $3.70 (3.32-4.12) per YOLS. For <$4 per YOLS, self-administration of aspirin within 4 hours of severe chest pain onset has the potential to save 13 000 lives per year in the US population. Benefits of reducing deaths post-AMI outweighed the risk of bleeding deaths from aspirin 10 times over.

Smallmouth Bass and Walleye predation on stocked age‐0 Walleye in Lake Oahe, South Dakota

AbstractObjectiveWalleye Sander vitreus are important sport fish that are commonly stocked to supplement populations. Increases in Smallmouth Bass Micropterus dolomieu abundance have prompted concerns regarding potential predation by these and other piscivores on stocked Walleye. Our objectives were to assess the timing and duration of predation on stocked Walleye, the frequency of occurrence and percent composition of Walleye in predator diets, and the percentage of stocked Walleye consumed.MethodsWe collected Smallmouth Bass, adult Walleye, Largemouth Bass M. nigricans, and Northern Pike Esox lucius diets in May (prestocking) and June–September (poststocking) 2019 and 2021 from three bays in Lake Oahe, South Dakota. We stocked two bays with Walleye (30–32 mm; 255–1649 Walleye/ha), whereas one bay was unstocked and served as a reference. We estimated Smallmouth Bass population abundance using Schnabel capture–recapture models, and we used bioenergetics to estimate the percentage of stocked age‐0 Walleye consumed.ResultWe found age‐0 Walleye in up to 11.4% of Smallmouth Bass diets and 14.6% of adult Walleye diets during the poststocking period. A single Largemouth Bass consumed one Walleye at 3 days poststocking (DPS), whereas we did not identify Walleye in Northern Pike diets. Daily mean percent composition by weight (±95% confidence interval) of age‐0 Walleye in diets peaked at 43.2 ± 35.1% at 3 DPS for Smallmouth Bass and 49.8 ± 97.7% at 14 DPS for adult Walleye. Following the peaks, age‐0 Walleye percent composition by weight rapidly declined and was generally 0% after 25 DPS. Smallmouth Bass abundance was 0.4–5.6 fish/ha, whereas recaptures of other predator species were insufficient for reliable population estimates. We estimated that Smallmouth Bass consumed 29,930 age‐0 Walleye in 2019 and 12,535 age‐0 Walleye in 2021 (up to 14.7 ± 4.7% of stocked fish), potentially representing an important source of stocking mortality.ConclusionOur research provides insights into the effects of poststocking predation on age‐0 Walleye by Smallmouth Bass and, to a lesser extent, Walleye, Largemouth Bass, and Northern Pike. Managers should consider predation on stocked fingerling Walleye from resident predators and should contemplate alternative stocking locations or timing to reduce potential predation.

The effectiveness of the semi‐automated Identifin software to accurately fast‐track dorsal fin photographic identifications of sharks

Abstract For some marine species, photo‐identification (photo‐ID) data can be used to generate population estimates critical for conservation efforts. For the white shark (Carcharadon carcharias), different photo‐ID methods have been proposed: (1) the traditional manual matching method based on non‐organized databases, (2) the notches code method based on organized databases and (3) the semi‐automatic software, Identifin. However, the effectiveness of these different methods and the applicability to other shark species have not been adequately explored. Eleven inexperienced and two experienced investigators used the three different photo‐ID methods to record the accuracy and time taken to identify individual white sharks from photo‐ID images. Both the traditional and notches code methods allowed for the accurate matching of individuals to the databases provided. For all investigators, the notches code method used significantly less time (14 min ± 0.14 min) than the traditional matching method (19 min ± 1.34 min). The semi‐automated method, Identifin, further shortened the identification time to 2 min (± 0.10 min) and provided a significantly higher matching accuracy (96% correct matches) compared with traditional manual matching (78% correct matches) and the notches code method (70% correct matches). The use of Identifin was tested to identify bronze whaler sharks (Carcharhinus brachyurus), a species with finer notches patterns when compared with white sharks. Identifin showed less efficiency in matching individual photographs to the database, but when very‐high‐quality (VHQ) photographs were available, matching improved substantially. Identifin software shows great potential in assisting researchers to accurately identify individual sharks in large databases, and this can contribute significantly to the conservation of shark species. The software and automated process need to be adapted to be functional on a variety of different shark species, but it proves to be an effective tool in managing large photo‐ID databases.

ESTIMATION POPULATION SIZE PECCARIES (TAYASSU PECARI), IN THE “RIO NEGRO” FARM - BRASILIAN PANTANAL, DURING 2003 - 2004, BY MEANS CAPTURE AND RECAPTURE MULTIPLE METHOD

The Tayassu pecari are predominantly distributed in conserved biomes and the maintenance of the species is very susceptible to human activity. In this context, it is important the search for methods of population estimation as well as apply robust methods that allow more accurate estimative. Therefore, this work aims to estimate the population of peccaries, on the Rio Negro farm (Aquidauana-MS) through the multiple captures and recapture method during the years 2003 and 2004, considering the assumption that the population is closed. The estimate of the population size was obtained by the computational resampling and three procedures are compared. It was verified the marked difference between males and females for both years. The population size it was estimated in 134 and 192, however, by means the bootstrap method, a notable change in the distribution pattern of estimates was verified, being positively asymmetric and symmetric, for 2003 and 2004 respectively.

CNN 기반 위성 이미지를 활용한 북한의 도시 인구추정

North Korea does not officially disclose population data through formal procedures. However, information related to North Korea's population can be verified through KOSTAT or internet searches. Nevertheless, these data are based on population surveys conducted with the support of the United Nations Population Fund (UNFPA) in 1993 and 2008, and are known to be of questionable reliability. In this study, as an initial attempt to estimate the current population of North Korea, we utilized daytime satellite images from 2023 to estimate the populations of Pyongyang and Kaesong at the grid level. The research resulted in the development of a gridded population estimation model based on a Convolutional Neural Network (CNN). The model was trained on CNN using data from South Korea and aimed to be applied to North Korea. It employed the VGG16 model, a representative algorithm of CNN, for transfer learning. To account for seasonal differences in the images from daytime satellite data, a U-net was used for image adjustment. Furthermore, neighboring effects were incorporated to enhance the model's performance. The model fitting results indicated that the populations of the four major metropolitan cities in South Korea were estimated without significant differences from actual populations. The populations of Pyongyang and Kaesong in North Korea were also estimated to be similar to the 2008 census data, demonstrating satisfactory results.

Age Estimation by Machine Learning and CT-Multiplanar Reformation of Cranial Sutures in Northern Chinese Han Adults.

To establish age estimation models of northern Chinese Han adults using cranial suture images obtained by CT and multiplanar reformation (MPR), and to explore the applicability of cranial suture closure rule in age estimation of northern Chinese Han population. The head CT samples of 132 northern Chinese Han adults aged 29-80 years were retrospectively collected. Volume reconstruction (VR) and MPR were performed on the skull, and 160 cranial suture tomography images were generated for each sample. Then the MPR images of cranial sutures were scored according to the closure grading criteria, and the mean closure grades of sagittal suture, coronal sutures (both left and right) and lambdoid sutures (both left and right) were calculated respectively. Finally taking the above grades as independent variables, the linear regression model and four machine learning models for age estimation (gradient boosting regression, support vector regression, decision tree regression and Bayesian ridge regression) were established for northern Chinese Han adults age estimation. The accuracy of each model was evaluated. Each cranial suture closure grade was positively correlated with age and the correlation of sagittal suture was the highest. All four machine learning models had higher age estimation accuracy than linear regression model. The support vector regression model had the highest accuracy among the machine learning models with a mean absolute error of 9.542 years. The combination of skull CT-MPR and machine learning model can be used for age estimation in northern Chinese Han adults, but it is still necessary to combine with other adult age estimation indicators in forensic practice.

Alterations in cell arrangements of group B streptococcus due to virulence factor expression can bias estimates of bacterial populations based on colony count measures.

Group B streptococcus (GBS) is a chain-forming commensal bacterium and opportunistic pathogen that resides in the gastrointestinal and genitourinary tract of healthy adults. GBS can cause various infections and related complications in pregnant and nonpregnant women, adults, and newborns. Investigations of the mechanisms by which GBS causes disease pathogenesis often utilize colony count assays to estimate bacterial population size in experimental models. In other streptococci, such as group A streptococcus and pneumococcus, variation in the chain length of the bacteria that can occur naturally or due to mutation can affect facets of pathogenesis, such as adherence to or colonization of a host. No studies have reported a relationship between GBS chain length and pathogenicity. Here, we used GBS strain 874391 and several derivative strains displaying longer chain-forming phenotypes (874391pgapC, 874391ΔcovR, 874391Δstp1) to assess the impact of chain length on bacterial population estimates based on the colony-forming unit (c.f.u.) assay. Disruption of GBS chains via bead beating or sonication in conjunction with fluorescence microscopy was used to compare chaining phenotypes pre- and post-disruption to detect long- and short-chain forms, respectively. We used a murine model of GBS colonization of the female reproductive tract to assess whether chaining may affect bacterial colonization dynamics in the host during chronic infection in vivo. Overall, we found that GBS exhibiting long-chain form can significantly affect population size estimates based on the colony count assay. Additionally, we found that the length of chaining of GBS can affect virulence in the reproductive tract colonization model. Collectively, these findings have implications for studies of GBS that utilize colony count assays to measure GBS populations and establish that chain length can affect infection dynamics and disease pathogenesis for this important opportunistic pathogen.

Estimating spawning green sturgeon (Acipenser medirostris Ayres, 1854) abundance in the Sacramento River using side-scan sonar and N-mixture models

Current estimates of the threatened southern distinct population segment of the North American green sturgeon ( Acipenser medirostris) combine a plot-sampling density estimator with Dual frequency IDentification SONar (DIDSON) and adaptive resolution imaging sonar (ARIS) sonar data. From 2020 to 2022, we annually collected images of all known green sturgeon aggregations and compared the established method to an N-mixture model using side-scan sonar images. We compared 18 different N-mixture model combinations and chose an overdispersed Poisson model that produced estimated abundances of 742, 1286, and 1208 for 2020–2022, respectively. These numbers are ∼2 times greater than the previous method and, if sustained, would fulfill a key criterion for green sturgeon recovery. N-mixture models are known to be sensitive to violations of assumptions, such as the highly dispersed data from our study that caused serious issues, and we recommend practitioners make judicious use of overdispersion and goodness-of-fit tests and be able to identify parameter confounding between detectability and abundance estimates. For our green sturgeon, we recommend simpler population estimates and to focus future energy on reducing variability in the data collection process.

Supplementation of Alternanthera sissoo pellets on feed digestion, rumen fermentation, and protozoal population in Thai native beef cattle

The objective of this experiment was to study the effects of Brazilian spinach (Alternanthera sissoo) pellet (BSP) supplementation on rumen fermentation, protozoal population, and methane (CH4) estimation in beef cattle. Four male Thai native beef cattle, 3 years old, with an average bodyweight of 180 ± 5 kg, were randomly arranged in a 4 × 4 Latin square design. The cattle were supplemented (on-top) with four levels of BSP (2, 4, 6, and 8% dry matter intake (DMI), respectively). The roughage component, derived from rice straw, was fed at 40 % of DMI, while the concentrate diet was fed at 60 % of DMI. The result of the experiment demonstrated that BSP supplementation had no effect on the DMI, nutrient intake, or nutrient digestibility (p > 0.05). Rumen pH and ammonia-nitrogen concentration were not significant, while the average protozoal population linearly decreased (p = 0.002) with BSP supplementation. Mean blood urea-nitrogen concentration was linearly increased (p = 0.004) when increasing the level of BSP. Brazilian spinach pellet had no significant effect on total volatile fatty acids (TVFA), VFA profiles, and CH4 estimation (p > 0.05). Nitrogen balance was no different from the supplementation of BSP. The study indicates that Brazilian spinach pellet supplementation showed no noticeable effects on feed intake, rumen parameters, and nitrogen utilization; however, at 6–8% of DMI, there was a decrease in protozoal population, with no corresponding reduction in CH4 estimation.