Abundance Estimates Research Articles

Absolute Abundance Estimates of Atlantic Goliath Grouper (Epinephelus itajara) on Spawning Aggregation Sites

Reliable data on Atlantic Goliath Grouper abundance are prerequisite to informed management decisions, particularly as the State of Florida reopened a limited harvest on the species in 2023 after a 32-year moratorium. Limited data exist for this purpose and fisheries data have been unavailable for over three decades due to a fishery closure that began in 1990. The purpose of this study was to compare absolute abundance estimates of Goliath Grouper between two years using an efficient, cost-effective method developed by Koenig. An underwater tagging method was used to collect mark and resight data for use in a Peterson deterministic model. These data were collected at the same spawning aggregation sites off Jupiter, Florida near the time of the new moon in September 2013 and August 2022. We found that Goliath Grouper abundance had declined at all but one of six sites since 2013. Because data were not collected during the intervening years, interannual variability is unknown. However, given the highly age-structured spawning stock of adult Goliath Grouper on the spawning grounds, the lower abundances measured in 2022 may reflect a real decline in the population rather than just representing a weak year of adult recruitment to these spawning sites.

A multidisciplinary approach to estimating wolf population size for long-term conservation.

The wolf (Canis lupus) is among the most controversial of wildlife species. Abundance estimates are required to inform public debate and policy decisions, but obtaining them at biologically relevant scales is challenging. We developed a system for comprehensive population estimation across the Italian alpine region (100,000km2 ), involving 1513 trained operators representing 160 institutions. This extensive network allowed for coordinated genetic sample collection and landscape-level spatial capture-recapture analyses that transcended administrative boundaries to produce the first estimates of key parameters for wolf population status assessment. Wolf abundance was estimated at 952 individuals (95% credible interval 816-1120) and 135 reproductive units (i.e., packs) (95% credible interval 112-165). We also estimated that mature individuals accounted for 33-45% of the entire population. The monitoring effort was spatially estimated thereby overcoming an important limitation of citizen science data. This is an important approach for promoting wolf-human coexistence based on wolf abundance monitoring and an endorsement of large-scale harmonized conservation practices.

Acoustic density estimates of beaked whales off the mid-Atlantic coast of the USA in winter and spring

Increasing amounts of noise have been introduced into the marine environment by commercial, military and recreational activities over recent decades. Ziphiids (beaked whales in the Family Ziphiidae) are particularly sensitive to anthropogenic noise, which can lead to behavioural and physiological changes that may cause death in extreme cases. Despite these concerns, there are significant gaps in our knowledge of ziphiid distribution and density in areas exposed to noise. This study presents data from acoustic and visual vessel surveys conducted across the Outer Continental Shelf of North and South Carolina and southern Virginia in the USA (NOAA permits 14,809-03 and 16,473) with the aim of addressing data gaps for this region in spring and winter. Echolocation click trains were attributed to either Cuvier's (Ziphius cavirostris) or Gervais' (Mesoplodon europaeus) beaked whales based on peak frequency, 3 dB and 10 dB bandwidths, and inter-click interval. Estimates of click depth were used to correct estimates of perpendicular distance and improve detection functions used in Multiple Covariate Distance Sampling. Availability bias was quantified using tag data from other regions modified with local dive data. Swell height and sea surface temperature were found to affect the detection function and were therefore included in the final model. Incorporating cruise identity (winter vs. spring), candidate species (Cuvier's vs. Gervais' beaked whale) and/or cluster size did not improve model fit, suggesting there was no discernible seasonal effect, variation in detectability by species or increased probability of detection for larger groups. Design-based estimates of global beaked whale density (1.64 individuals per 100 km2: CI 0.88–3.03) and abundance (2963: CI 1597-5497) were then made incorporating a g(0) estimate of 0.43. These represent the first abundance estimates made for ziphiids using a towed hydrophone array off the USA's eastern seaboard. A Density Surface Model suggested slope and Sea Surface Temperature may influence ziphiid density in the region. This study provides seasonal data on deep diving beaked whales that can be used to inform management decisions regarding anthropogenic activities in this region.

Integrating assemblage structure and habitat mapping data into the design of a multispecies reef fish survey

AbstractObjectiveSince 2010, three spatially disjunct reef fish video surveys have provided fishery‐independent data critical to the assessment and management of reef fishes in the Gulf of Mexico. Although analytical approaches have recently been developed to integrate data from these surveys into a single measure of relative abundance and size composition, a more parsimonious approach would be to integrate survey efforts under a single Gulf‐wide survey design. Accordingly, we conducted a retrospective analysis of historical video‐ and habitat‐mapping data to develop a novel stratified random sampling design for conducting surveys of natural and artificial reef habitats.MethodsWe conducted a series of classification and regression tree analyses to delineate both spatial and habitat strata, and conducted simulations to assess the performance of an optimized survey design.ResultSpatially, classification and regression tree results identified three depth strata (10–25 m, >25–50 m, >50–180 m) and three regional strata (north‐central Gulf, Big Bend, southwest Florida) in the eastern Gulf. For both natural and artificial reefs, habitat strata were delineated based on a combination of relative relief (low, medium, high) and size of the individual reef feature, although reef scale differed markedly between natural (<100 m2, 100–1000 m2, >1000 m2) and artificial habitats (<25 m2, 25–100 m2, >100 m2). To optimize effort among sampling strata, effort was allocated proportionally based on a combination of habitat availability and managed‐species richness for each stratum. Simulation results indicated that relative median biases were <10% and relative median absolute deviations <30% on estimates of abundance for most species examined on natural reefs under the optimal design, except Greater Amberjack Seriola dumerili. These measures of bias and imprecision were similar or higher for most species simulated using simple random and stratified random survey designs. Estimated relative median bias and relative median absolute deviations were notably higher for artificial reef surveys.ConclusionBased on these results, survey efforts were integrated as the Gulf Fishery Independent Survey of Habitat and Ecosystem Resources (G‐FISHER) in 2020.

IS-Seq: a bioinformatics pipeline for integration sites analysis with comprehensive abundance quantification methods

BackgroundIntegration site (IS) analysis is a fundamental analytical platform for evaluating the safety and efficacy of viral vector based preclinical and clinical Gene Therapy (GT). A handful of groups have developed standardized bioinformatics pipelines to process IS sequencing data, to generate reports, and/or to perform comparative studies across different GT trials. Keeping up with the technological advances in the field of IS analysis, different computational pipelines have been published over the past decade. These pipelines focus on identifying IS from single-read sequencing or paired-end sequencing data either using read-based or using sonication fragment-based methods, but there is a lack of a bioinformatics tool that automatically includes unique molecular identifiers (UMI) for IS abundance estimations and allows comparing multiple quantification methods in one integrated pipeline.ResultsHere we present IS-Seq a bioinformatics pipeline that can process data from paired-end sequencing of both old restriction sites-based IS collection methods and new sonication-based IS retrieval systems while allowing the selection of different abundance estimation methods, including read-based, Fragment-based and UMI-based systems.ConclusionsWe validated the performance of IS-Seq by testing it against the most popular analytical workflow available in the literature (INSPIIRED) and using different scenarios. Lastly, by performing extensive simulation studies and a comprehensive wet-lab assessment of our IS-Seq pipeline we could show that in clinically relevant scenarios, UMI quantification provides better accuracy than the currently most widely used sonication fragment counts as a method for IS abundance estimation.

Evaluation of replicate sampling using hierarchical spatial modeling of population surveys accounting for imperfect detectability

AbstractEffective species management and conservation benefit from knowledge of species distribution and status. Surveys to obtain that information often involve replicate sampling, which increases survey effort and costs. We simultaneously modeled species distribution, abundance and spatial correlation, and compared the uncertainty in replicate abundance estimates of the endangered palila (Loxioides bailleui) using hierarchical generalized additive models with a soap film smoother that incorporated random effects for visit. Based on survey coverage and detections, we selected the 2017 point‐transect distance sampling survey on Mauna Kea, Hawai‘i Island, for our modeling. Our modeling approach allowed us to account for imperfect detections, control the effects of boundary features, and generate visit‐specific density surface maps. We found that visit‐specific smooths were nearly identical, indicating that little information was gained from a subsequent visit, and that most of the estimator uncertainty was derived from within‐visit variability. Scaling back the palila survey to a single visit would halve the survey effort and logistical costs and increase efficiencies in data management and processing. Changing the sampling protocol warrants careful consideration and our findings may help management and regulatory agencies by maximizing efficiency and minimizing costs of surveying protocols, while providing guidelines on how to best collect information critical to species' conservation.

Distribution and Abundance of California (Zalophus californianus) and Steller (Eumetopias jubatus) Sea Lions in the Inshore Waters of Washington, 2013-2016

Two species of sea lions occur in the in387land waters of Washington State: the California sea lion (Zalophus californianus) and the Steller sea lion (Eumetopias jubatus). Both species breed elsewhere, but they typically move into Puget Sound and adjacent waters of the Salish Sea from autumn through spring. There is a need for information on their current abundance and seasonal use patterns as both species prey heavily on threatened/endangered stocks of salmon and steelhead trout (Oncorhynchus spp.), and empirical abundance estimates of these species are lacking for inland Washington waters. From 2013 to 2016, we conducted 39,399 km of aerial surveys for marine mammals in this area, sighting 255 groups of sea lions. We used a subset of 7,841 km of effort and 165 sea lion sightings made during surveys in good sighting conditions to estimate in-water abundance using line-transect methods. Historical tagging data collected in Pacific Northwest waters were used to evaluate the proportions of time that each species spent on land and conducting dives, and then to develop correction factors to derive total abundance for both sea lion species, providing the first empirical abundance estimates for these waters. We estimated that between 33 and 442 California sea lions were found in Puget Sound/Hood Canal in different seasons, with nearly 3,000 being found in the broader inland Washington waters in the peak season (spring). Steller sea lions occurred in much smaller numbers, with a peak of 219 animals in Puget Sound/Hood Canal/Strait of Juan de Fuca in autumn (and possibly as many as 600 to 700 in the entire study area). While some estimates suffer from low precision, this study demonstrates that substantial numbers of sea lions use waters of the study area throughout much of the year. Our results provide an important step toward a better understanding of these two species in the inland waters of Washington, as well as their potential effects on protected salmonid prey species.

Pooling of intra-site measurements inflates variability of the correlation between environmental DNA concentration and organism abundance.

Environmental DNA (eDNA) analysis can promote efficient ecosystem monitoring and resource management. However, limited knowledge of the factors affecting the relationship between eDNA concentration and organism abundance causes uncertainty in relative abundance estimates based on eDNA concentration. Pooling of data points obtained from multiple locations within a site has been used to mitigate intra-site variation in eDNA and abundance estimates, but decreases the sample size used for estimating the relationship. I here assessed how the pooling of intra-site measurements of eDNA concentration and organism abundance impacted the reliability of the correlative relationship between eDNA concentration and organism abundance. Mathematical models were developed to simulate measurements of eDNA concentrations and organism abundances from multiple locations in a given survey site, and the CVs (coefficient of variability) of the correlations were compared depending on whether data points from different locations were individually treated or pooled. Although the mean and median values of the correlation coefficients were similar between the scenarios, the CVs of the simulated correlations were substantially higher under the pooled scenario than the individual scenario. Additionally, I re-analyzed two empirical studies conducted in lakes, both showing higher CVs of the correlations by pooling intra-site measurements. This study suggests that it would make eDNA-based abundance estimation more reliable and reproducible to individually analyze target eDNA concentrations and organism abundance estimates.

A review of an emerging tool to estimate population parameters: the close-kin mark-recapture method

Knowing the number of individuals in a population is fundamental for the sustainable management of exploited marine resources but estimating this parameter is often extremely challenging, especially in large, highly mobile and dispersed populations. Abundance estimation traditionally relies on multiple data types that include the relationship between fishery catches and effort (Catch Per Unit Effort or CPUE), scientific research surveys and demographic models that are developed to estimate past and current stock dynamics, but uncertainty is often high. Close-kin mark-recapture (CKMR) is an alternative method for estimating abundance and other demographic parameters (e.g. population trend, survival rates, connectivity), using kinship relationships determined from genetic samples. This methodology is based on a simple concept - the larger the population the less likely to find relatives and vice versa - and was proposed two decades ago although regained considerable attention recently. Refinements in the statistical methodology and advances in high throughput sequencing methods have boosted the efficiency of genomic analysis, promising to revolutionize the field of fisheries stock assessments. In theory, it can be applied to almost any species, provided that there is sufficient information about the life-history/biology of the organism and that the populations are not so small as to be almost extinct or so large that finding relatives becomes extremely difficult. Thus, it has the potential to provide baseline data for the many exploited fish stocks that remain largely unassessed and to reduce uncertainty in those that are regularly evaluated. Here, we provide an overview of the method in the context of fisheries assessments, analyze the advances and synthetize the field studies published in the last five years. Moreover, we evaluate the readiness, viability and maturity of the method to infer demographic parameters in species spanning diverse life histories. We evaluate technical considerations and requirements for a successful application and analyze the main challenges and limitations preventing a broader implementation.

A comparison of survey method efficiencies for estimating densities of zebra mussels (Dreissena polymorpha).

Abundance surveys are commonly used to estimate plant or animal densities and frequently require estimating detection probabilities to account for imperfect detection. The estimation of detection probabilities requires additional measurements that take time, potentially reducing the efficiency of the survey when applied to high-density populations. We conducted quadrat, removal, and distance surveys of zebra mussels (Dreissena polymorpha) in three central Minnesota lakes and determined how much survey effort would be required to achieve a pre-specified level of precision for each abundance estimator, allowing us to directly compare survey design efficiencies across a range of conditions. We found that the required sampling effort needed to achieve our precision goal depended on both the survey design and population density. At low densities, survey designs that could cover large areas but with lower detection probabilities, such as distance surveys, were more efficient (i.e., required less sampling effort to achieve the same level of precision). However, at high densities, quadrat surveys, which tend to cover less area but with high detection rates, were more efficient. These results demonstrate that the best survey design is likely to be context-specific, requiring some prior knowledge of the underlying population density and the cost/time needed to collect additional information for estimating detection probabilities.

Pragmatic Considerations When Extracting DNA for Metagenomics Analyses of Clinical Samples.

Microbiome analyses are essential for understanding microorganism composition and diversity, but interpretation is often challenging due to biological and technical variables. DNA extraction is a critical step that can significantly bias results, particularly in samples containing a high abundance of challenging-to-lyse microorganisms. Taking into consideration the distinctive microenvironments observed in different bodily locations, our study sought to assess the extent of bias introduced by suboptimal bead-beating during DNA extraction across diverse clinical sample types. The question was whether complex targeted extraction methods are always necessary for reliable taxonomic abundance estimation through amplicon sequencing or if simpler alternatives are effective for some sample types. Hence, for four different clinical sample types (stool, cervical swab, skin swab, and hospital surface swab samples), we compared the results achieved from extracting targeted manual protocols routinely used in our research lab for each sample type with automated protocols specifically not designed for that purpose. Unsurprisingly, we found that for the stool samples, manual extraction protocols with vigorous bead-beating were necessary in order to avoid erroneous taxa proportions on all investigated taxonomic levels and, in particular, false under- or overrepresentation of important genera such as Blautia, Faecalibacterium, and Parabacteroides. However, interestingly, we found that the skin and cervical swab samples had similar results with all tested protocols. Our results suggest that the level of practical automation largely depends on the expected microenvironment, with skin and cervical swabs being much easier to process than stool samples. Prudent consideration is necessary when extending the conclusions of this study to applications beyond rough estimations of taxonomic abundance.

Eastern High Arctic–Baffin Bay beluga whale (Delphinapterus leucas) estuary abundance and use from space

IntroductionThe Eastern High Arctic–Baffin Bay (EHA-BB) beluga whale (Delphinapterus leucas) population spends summer in estuaries around Somerset Island, Nunavut, Canada. A single abundance estimate from 1996 suggests an abundance >21,000 beluga whales; however, more information on abundance and distribution is needed to ensure effective management of this population, especially in estuaries where previous surveys provided minimal coverage. To assess the feasibility of using Very High Resolution (VHR) satellite imagery to obtain estuary abundance estimates for this beluga population, we evaluated a citizen science crowd counting initiative that was designed to monitor remote beluga whale populations and their estuary use.MethodsIn July and August 2020 the WorldView 2 and 3, and GeoEye 1 satellites were tasked to collect VHR imagery (30–41 cm) of estuaries previously known to be used by Eastern High Arctic–Baffin Bay beluga whales. The objectives were to obtain an estuary abundance estimate for this population from satellite imagery, and to evaluate the effectiveness of having imagery annotated using a crowd-source platform. Almost 3,800 km2of ocean imagery was analyzed using Maxar’s Geospatial Human Imagery Verification Effort (GeoHIVE) Crowdsourcing platform. Expert readers then manually compared counts to those performed by crowd-counters to determine variance in observer counts.Results and DiscussionThe estuary abundance estimate from 11 core estuaries was 12,128 (CV 36.76%, 95% confidence interval 6,036–24,368) beluga whales. This represents an estuary abundance estimate only, as the greater Peel Sound and Prince Regent Inlet areas were not photographed. The estuaries with the largest abundance of beluga whales were Creswell Bay, Maxwell Bay, and Prince Whales Island, with over 2,000 crowd-counted whales in each estuary. Although VHR imagery has potential to assist with surveying and monitoring marine mammals, for larger estuaries it was not always possible to photograph the entire area in a single day, and cloud cover was an issue for sections of most images. This work will assist with planning large-scale aerial surveys for monitoring beluga whale populations, identifying high-use areas and important beluga habitat, and highlights the utility of using VHR imagery to enhance our understanding of estuary abundance and distribution of Arctic whales.

Leveraging hunters as citizen scientists for monitoring non‐target species

Abstract Hunter populations can provide a tremendous workforce of citizen scientists afield when queried for data. Soliciting incidental observations of non‐target species from hunters may be a relatively important but untapped population monitoring resource in systems where hunter effort is common and widespread. During 2012–2016, we queried hunters of deer and elk for observations of a non‐target species, moose, across their statewide distribution in Montana. We analysed data in an abundance‐detection framework with n‐mixture models and evaluated the effects of covariates such as hunter effort, survey response totals, weekly session and forest cover on detection probability before using models to predict moose abundance. We collected an average of 3409 moose observations per year and our best n‐mixture model included effects of week, year (number of responses), site (proportionate forest cover) and site‐year (hunter effort) on detection probability, as well as an effect of site (area of forest and shrub habitat) on abundance. Density estimates averaged 0.099 (range 0.002–0.439) moose/km2 across sites or 0.200 (range 0.017–0.799) moose/km2 when limited to density within shrub and forest cover specifically. Statewide abundance totals across the 5‐year study period averaged 10,755 (range 9925–11,620). Goodness‐of‐fit tests showed that models were identifiable and overdispersion of the data was low, yet some caution is still warranted when extrapolating these data to abundance estimates. Querying a sample of deer‐elk hunters for observations of a non‐target species yielded thousands of spatially georeferenced detections per year and analysis in a temporally structured framework yielded estimates of both detection probability and abundance. Abundance estimates at this scale are unprecedented for moose in Montana and are encouraging for long‐term monitoring over space and time.

Buckyball-metal Complexes as Potential Carriers of Astronomical Unidentified Infrared Emission Bands

Efforts over 40 yr still leave the source of astronomical infrared emission bands largely unidentified. Here, we report the first laboratory infrared (6–25 μm) spectra of gas-phase fullerene-metal complexes, [C60-Metal]+ (Metal = Fe, V) and show with density functional theory calculations that complexes of C60 with cosmically abundant metals, including Li, Na, K, Mg, Ca, Al, V, and Fe, all have similar spectral patterns. Comparison with observational infrared spectra from several fullerene-rich planetary nebulae demonstrates a strong positive linear cross-correlation. The infrared features of [C60-Metal]+ coincide with four bands attributed earlier to neutral C60 bands and in addition also with several bands unexplained to date. Abundance and collision theory estimates indicate that [C60-Metal]+ could plausibly form and survive in astrophysical environments. Hence, [C60-Metal]+ are proposed as promising carriers, in supplement to C60, of observational bands, potentially representing the largest molecular species in space other than C60, C60 +, and C70.

RawHash: enabling fast and accurate real-time analysis of raw nanopore signals for large genomes.

Nanopore sequencers generate electrical raw signals in real-time while sequencing long genomic strands. These raw signals can be analyzed as they are generated, providing an opportunity for real-time genome analysis. An important feature of nanopore sequencing, Read Until, can eject strands from sequencers without fully sequencing them, which provides opportunities to computationally reduce the sequencing time and cost. However, existing works utilizing Read Until either (i) require powerful computational resources that may not be available for portable sequencers or (ii) lack scalability for large genomes, rendering them inaccurate or ineffective. We propose RawHash, the first mechanism that can accurately and efficiently perform real-time analysis of nanopore raw signals for large genomes using a hash-based similarity search. To enable this, RawHash ensures the signals corresponding to the same DNA content lead to the same hash value, regardless of the slight variations in these signals. RawHash achieves an accurate hash-based similarity search via an effective quantization of the raw signals such that signals corresponding to the same DNA content have the same quantized value and, subsequently, the same hash value. We evaluate RawHash on three applications: (i) read mapping, (ii) relative abundance estimation, and (iii) contamination analysis. Our evaluations show that RawHash is the only tool that can provide high accuracy and high throughput for analyzing large genomes in real-time. When compared to the state-of-the-art techniques, UNCALLED and Sigmap, RawHash provides (i) 25.8× and 3.4× better average throughput and (ii) significantly better accuracy for large genomes, respectively. Source code is available at https://github.com/CMU-SAFARI/RawHash.

A standardized quantitative analysis strategy for stable isotope probing metagenomics.

Stable isotope probing (SIP) facilitates culture-independent identification of active microbial populations within complex ecosystems through isotopic enrichment of nucleic acids. Many DNA-SIP studies rely on 16S rRNA gene sequences to identify active taxa, but connecting these sequences to specific bacterial genomes is often challenging. Here, we describe a standardized laboratory and analysis framework to quantify isotopic enrichment on a per-genome basis using shotgun metagenomics instead of 16S rRNA gene sequencing. To develop this framework, we explored various sample processing and analysis approaches using a designed microbiome where the identity of labeled genomes and their level of isotopic enrichment were experimentally controlled. With this ground truth dataset, we empirically assessed the accuracy of different analytical models for identifying active taxa and examined how sequencing depth impacts the detection of isotopically labeled genomes. We also demonstrate that using synthetic DNA internal standards to measure absolute genome abundances in SIP density fractions improves estimates of isotopic enrichment. In addition, our study illustrates the utility of internal standards to reveal anomalies in sample handling that could negatively impact SIP metagenomic analyses if left undetected. Finally, we present SIPmg, an R package to facilitate the estimation of absolute abundances and perform statistical analyses for identifying labeled genomes within SIP metagenomic data. This experimentally validated analysis framework strengthens the foundation of DNA-SIP metagenomics as a tool for accurately measuring the in situ activity of environmental microbial populations and assessing their genomic potential. IMPORTANCE Answering the questions, "who is eating what?" and "who is active?" within complex microbial communities is paramount for our ability to model, predict, and modulate microbiomes for improved human and planetary health. These questions can be pursued using stable isotope probing to track the incorporation of labeled compounds into cellular DNA during microbial growth. However, with traditional stable isotope methods, it is challenging to establish links between an active microorganism's taxonomic identity and genome composition while providing quantitative estimates of the microorganism's isotope incorporation rate. Here, we report an experimental and analytical workflow that lays the foundation for improved detection of metabolically active microorganisms and better quantitative estimates of genome-resolved isotope incorporation, which can be used to further refine ecosystem-scale models for carbon and nutrient fluxes within microbiomes.

The design of a camera-based fisheries-independent survey for untrawlable habitat in the Gulf of Alaska

Biomass and size composition estimates from the fishery independent biennial Alaska Fisheries Science Center Resource Assessment and Conservation Engineering Division’s Groundfish Assessment Program Gulf of Alaska bottom trawl survey are an integral component of stock assessments and management of fishes in the region. A substantial proportion of the seafloor in the Gulf of Alaska survey area consists of rocky, high-relief habitat that is not accessible to trawl survey gear and is important habitat for many harvested fish species, especially rockfishes (Sebastes spp.). Survey estimates of groundfish abundance from trawlable grounds are expanded across the entire region. Therefore, survey abundance estimates could potentially be biased as a result of sampling that does not spatially represent all of the available habitat circumscribed by the Gulf of Alaska study area. Mapping the extent of the untrawlable habitat is a critical step toward understanding the scale of these potential biases and would benefit the design of a future untrawlable habitat survey. Several previous efforts have provided trawlability maps for part or all of the Gulf of Alaska based on different data inputs. In the present work, we compile two previously published untrawlable habitat maps with three other relevant data sources to create a new untrawlable habitat map, and use this map in conjunction with density estimates from existing underwater camera studies to investigate the feasibility of an untrawlable habitat rockfish survey in the Gulf of Alaska. An analysis of 1 km2 grids sampled more than once with a lowered camera system suggested that a single-stage sampling design (one camera transect per grid) would be most effective. Post-stratification analysis showed that either a simple depth stratification or stratification based on species distribution models provided lower coefficient of variation (CV) values at a given sample size compared to random sampling. Furthermore, a target CV of 25 % could be reached for a camera survey of dusky rockfish, northern rockfish, or Pacific ocean perch with less than 200 lowered camera transects if a stratification scheme based on species distribution models was used.

Tourism-supported working lands sustain a growing jaguar population in the Colombian Llanos

Understanding large carnivore demography on human-dominated lands is a priority to inform conservation strategies, yet few studies examine long-term trends. Jaguars (Panthera onca) are one such species whose population trends and survival rates remain unknown across working lands. We integrated nine years of camera trap data and tourist photos to estimate jaguar density, survival, abundance, and probability of tourist sightings on a working ranch and tourism destination in Colombia. We found that abundance increased from five individuals in 2014 to 28 in 2022, and density increased from 1.88 ± 0.87 per 100 km2 in 2014 to 3.80 ± 1.08 jaguars per 100 km2 in 2022. The probability of a tourist viewing a jaguar increased from 0% in 2014 to 40% in 2020 before the Covid-19 pandemic. Our results are the first robust estimates of jaguar survival and abundance on working lands. Our findings highlight the importance of productive lands for jaguar conservation and suggest that a tourism destination and working ranch can host an abundant population of jaguars when accompanied by conservation agreements and conflict interventions. Our analytical model that combines conventional data collection with tourist sightings can be applied to other species that are observed during tourism activities.Entender los patrones demográficos de los grandes carnívoros al interior de paisajes antrópicos es fundamental para el diseño de estrategias de conservación efectivas. En el Neotrópico, el jaguar (Panthera onca) es una de estas especies cuyas tendencias poblacionales y tasas de supervivencia en paisajes productivos son desconocidas. Para entender mejor estas dinámicas, integramos nueve años de fototrampeo junto a fotos de turistas para estimar la densidad, supervivencia, abundancia y probabilidad de avistamiento de esta especie en una finca ganadera y destino turístico en Colombia. Entre 2014 y 2022 encontramos que la abundancia incrementó de cinco a 28 individuos y la densidad de 1.88 ± 0.87 jaguares/ 100 km2 a 3.80 ± 1.08 jaguares/ 100 km2. La probabilidad de avistamiento por turistas aumentó de 0% en 2014 a 40% en 2020 antes de la pandemia del Covid-19. Nuestros resultados presentan las primeras estimaciones robustas de abundancia y supervivencia de este felino en paisajes antrópicos dónde el manejo de sistemas productivos combinados con turismo e intervenciones para la mitigación del conflicto puede albergar poblaciones abundantes de jaguares, demostrando su importancia para la conservación de esta especie. Nuestro modelo, al combinar datos convencionales con avistamientos, podría ser aplicado a otras especies observadas durante actividades turísticas.

Modelling Spectral Unmixing of Geological Mixtures: An Experimental Study Using Rock Samples

Spectral unmixing of geological mixtures, such as rocks, is a challenging inversion problem because of nonlinear interactions of light with the intimately mixed minerals at a microscopic scale. The fine-scale mixing of minerals in rocks limits the sensor’s ability to identify pure mineral endmembers and spectrally resolve these constituents within a given spatial resolution. In this study, we attempt to model the spectral unmixing of two rocks, namely, serpentinite and granite, by acquiring their hyperspectral images in a controlled environment, having uniform illumination, using a laboratory-based imaging spectroradiometer. The endmember spectra of each rock were identified by comparing a limited set of pure hyperspectral image pixels with the constituent minerals of the rocks based on their diagnostic spectral features. A series of spectral unmixing paradigms for explaining geological mixtures, including those ranging from simple physics-based light interaction models (linear, bilinear, and polynomial models) to classification-based models (support vector machines (SVMs) and half Siamese network (HSN)), were tested to estimate the fractional abundances of the endmembers at each pixel position of the image. The analysis of the results of the spectral unmixing algorithms using the ground truth abundance maps and actual mineralogical composition of the rock samples (estimated using X-ray diffraction (XRD) analysis) indicate a better performance of the pure pixel-guided HSN model in comparison to the linear, bilinear, polynomial, and SVM-based unmixing approaches. The HSN-based approach yielded reduced errors of abundance estimation, image reconstruction, and mineralogical composition for serpentinite and granite. With its ability to train using limited pure pixels, the half-Siamese network model has a scope for spectrally unmixing rock samples of varying mineralogical composition and grain sizes. Hence, HSN-based approaches effectively address the modelling of nonlinear mixing in geological mixtures.

Abundance Estimates for Marsh Bird Species in the Columbia Wetlands, British Columbia, Canada

Abundance Estimates for Marsh Bird Species in the Columbia Wetlands, British Columbia, Canada