Abundance Estimates Research Articles

Cisco population characteristics in Wisconsin lakes in relation to lake‐ and landscape‐level factors

AbstractObjectiveDeclines in Cisco Coregonus artedi populations in some inland lakes have prompted assessments of Cisco occurrence and extirpation risk in relation to various stressors to identify refuge lakes and factors that promote Cisco persistence. However, most previous assessments have focused on presence–absence of Cisco rather than examining how population characteristics, such as relative abundance or growth, might change in relation to lake‐ and landscape‐level environmental factors. Consequently, our specific objectives were to identify important environmental factors explaining variation in Cisco relative abundance and growth and to determine whether population metrics describing size and age distributions were related to relative abundance in Wisconsin inland lakes.MethodsCisco were collected from 48 inland Wisconsin lakes during 2011–2015 using vertical monofilament gill nets and population‐specific relative abundance estimates (catch per unit effort [CPUE]) were quantified as the number of individuals per gill‐net night. Sagittal otoliths were removed from a subsample of Cisco for age estimation and growth was indexed as mean total length (TL; mm) at age 2. Length and age data were used to develop a suite of metrics describing size and age distributions of each population. Random forest models were used to evaluate relationships between 10 biologically relevant predictor variables representing variation in physical, climatic, catchment, and limnological characteristics and Cisco CPUE and growth. Pearson correlations were used to determine whether population characteristics were related to CPUE.ResultCisco populations exhibited large variation in relative abundance, growth, and size and age distributions. Best‐fit random forest models explained approximately 25% of the variation in Cisco CPUE and 46% of the variation in growth. Growing degree‐days and variables associated with availability, quality, and quantity of suitable oxythermal conditions were identified as important predictors of both Cisco CPUE and growth; CPUE was also identified as an important predictor of growth. Mean TL and mean TL at age 2 were negatively related to Cisco CPUE, whereas mean age, number of age‐classes present, and maximum observed age were positively related to CPUE.ConclusionOur results suggest that maintenance of suitable oxythermal habitat conditions may be critical to conserving abundant Cisco populations. Our assessment also provides insights on how Cisco populations may respond to environmental and anthropogenic stressors, which could aid ongoing and future conservation and management efforts in Wisconsin and elsewhere.

GAUSS: Guided encoder - decoder Architecture for hyperspectral Unmixing with Spatial Smoothness

ABSTRACT This study introduces GAUSS (Guided encoder-decoder Architecture for hyperspectral Unmixing with Spatial Smoothness), a novel autoencoder-based architecture for hyperspectral unmixing (HU). GAUSS consists of an Approximation Network (AN), Unmixing Network (UN), and a Mixing Network (MN). The AN incorporates spatial context within a hyperspectral pixel’s neighborhood, while the UN utilizes a pseudo-ground truth mechanism to enhance abundance estimation. The MN provides estimated endmembers’ signatures. By incorporating UN-produced abundances, unlike the conventional AE model, GAUSS overcomes the single-layer constraint of the MN. Thereafter, a secondary training phase improves the accuracy of endmembers and abundance estimation using a reliable Signal Processing (SP) algorithm, resulting in superior HU performance. The results demonstrate the effectiveness of GAUSS on two Standard datasets and a Simulated dataset compared to the state-of-the-art SP and Deep Learning (DL) based methods. This signifies the benefit of integrating an SP algorithm in the training process, contributing to advancements in DL-based HU techniques.

Nitrogen abundances of the Be-type stars in 30 Doradus

ABSTRACT A sub-set of the 67 Be-type stars observed in 30 Doradus during the VLT-FLAMES Tarantula Survey (VFTS) campaign have been analysed to estimate atmospheric parameters and chemical compositions, in particular their nitrogen abundance. Reliable results were found for 23 targets comprising the largest Large Magellanic Cloud sample currently available. The nitrogen abundance estimates have been compared with predictions from evolutionary models for rapidly rotating single stars (or non-interacting multiple systems) and for interacting binaries. The observations appear to be incompatible with all the targets having a single star evolutionary history. The results agree better with a binary evolutionary history with at least 30 per cent of the VFTS sample having apparently evolved by this pathway. These conclusions are consistent with a previous analysis of the ve sin i-estimates for this Be-type sample.

Does prey availability influence the detection of Dinophysis spp. by the imaging FlowCytobot?

The Imaging FlowCytobot (IFCB) is a field-deployable imaging-in-flow cytometer that is increasingly being used to monitor harmful algae. The IFCB acquires images of suspended particles based on their chlorophyll-a fluorescence and/or the amount of light they scatter (side scattering). The present study hypothesized that fluorescence-based image acquisition would undercount Dinophysis spp., a genus of non-constitutive mixotrophs, when prey is limited. This is because Dinophysis spp. acquire plastids via ingestion of their ciliate prey Mesodinium spp., and lose photosynthetic capacity and autofluorescence in the absence of prey. Even small blooms of Dinophysis spp. can be highly toxic and result in diarrhetic shellfish poisoning (DSP), highlighting the importance of accurately detecting low abundances. To explore this, laboratory experiments were conducted to determine optimal IFCB settings for a fed culture of Dinophysis acuminata, and an existing time series of IFCB observations collected in Puget Sound (Washington, U.S.A) was used to compare Dinophysis spp. abundance estimates from samples triggered via side scattering versus fluorescence in relation to Mesodinium spp. abundance. This study introduces a quantitative approach for optimizing the detection of target harmful algae which can be repeated across multiple IFCBs and demonstrates the effects of IFCB calibration on Dinophysis spp. detection. The laboratory experiments showed that IFCB settings for fluorescence-based image acquisition need to be fairly sensitive to accurately detect D. acuminata cells. A poorly calibrated IFCB can miss a significant proportion of D. acuminata abundance whatever the method used to trigger the image acquisition. Field results demonstrated that the physiological status of Dinophysis spp. can influence their detection by the IFCB when triggering on fluorescence. This was observed during a 7-day period when the IFCB failed to detect Dinophysis spp. cells when triggering on fluorescence while cells were still detected using the side scattering triggering method as well as observed by microscopy. During this period, Mesodinium spp. was not detected, IFCB-derived autofluorescence level of individual cells of Dinophysis spp. was low, and less than 50 % of Dinophysis spp. cells exhibited autofluorescence under the microscope. Together, this indicates that the unique feeding ecology of Dinophysis spp. may affect their detection by the IFCB when cells are starved.

Seasonal abundance estimates of cetaceans in the southern Black Sea (Sinop), Türkiye

AbstractThe availability of reliable information on the abundance and distribution of threatened species is fundamental to evaluating their conservation status and taking the necessary measures to implement effective management. The seasonal abundance and distribution of cetaceans in the Sinop region, one of the essential fishing areas of the Black Sea, were estimated with line‐transect data. Dedicated boat‐based visual observations were conducted in four seasons between May 2019 and March 2020. Average estimates of abundance in the region over all seasons were 1,058 individuals for Black Sea harbor porpoises (Phocoena phocoena relicta; CV = 19.25%, 95% CI[725, 1,542]), 188 individuals for Black Sea bottlenose dolphins (Tursiops truncatus ponticus; CV = 21.67%, 95% CI[123, 289]), and 311 individuals for Black Sea common dolphin (Delphinus delphis ponticus; CV = 16.77%, 95% CI[123, 427]). The highest estimates for all three species were obtained in the spring. Harbor porpoises and bottlenose dolphins were present in the study area throughout the year, while common dolphins left the region in winter. These findings offer valuable insights that can guide and inform future conservation strategies, aligning with national and international frameworks for the protection of these cetacean species.

Documentation of commercial and subsistence hunting of Critically Endangered black-and-white ruffed lemurs (Varecia variegata) in northeastern Madagascar

Hunting of wild animals for meat and habitat loss are the main drivers of wildlife population decline around the world, and in tropical regions in particular. While Madagascar is a hotspot for biodiversity, hunting is widespread, mostly in form of subsistence hunting, while hunting for the pet trade is less often reported.We studied hunting of the Critically Endangered black-and-white ruffed lemur (Varecia variegata) in northeastern Madagascar. Using lemur surveys (102.7 km survey effort) and 54 semi-structured and seven key informant interviews, we assessed the local knowledge, hunting pressure, and the perceived and actual abundances of V. variegata in two hunting and two non-hunting villages.V. variegata was well known (> 83%) by the respondents but abundance estimates differed significantly between hunting and non-hunting villages, with 26% and 77% of respondents, respectively, estimating a high abundance of ruffed lemurs in the adjacent forests of the villages. Actual observations of V. variegata also differed strongly, in accordance to perceived abundances. Hunting was either done by trapping animals or by pursuit hunts. In both hunting villages, adult lemurs were used for direct meat consumption and juveniles for rearing for the later trade. Hand-raised V. variegata were reported to be sold for 38–71 USD on regional markets or ‘delivered’ directly to buyers.While wildlife hunting has been widely reported from all over Madagascar, commercial hunting, hand-rearing and trading adds a new dimension of threat towards these Critically Endangered lemurs. As such, the extent of the trade is a priority for future studies.

Real-time discrimination of contamination source composed of multiple pollutants in surface water based on deep learning and UV–Vis spectral abundance estimation methodology

Water resources are one of the most important strategic resources for human survival and development. At present, surface water pollution incidents occur frequently, most of which are caused by enterprises' over-discharge, stolen discharge, and other activities to evade supervision. Automatic and rapid determination of pollution source types is conducive to further targeting pollution-causing enterprises and realizing scientific accountability in law enforcement. The existing method mainly adopts the pattern recognition method for pollution discrimination, which is only suitable for the situation of a single source of pollutant, and cannot identify the pollution for multiple pollution sources mixed surface water. To solve the problem of identification of mixed chemical pollutants in surface water pollution sources and identification of simultaneous emission of multiple pollution sources, a total pollution source analysis method based on spectral unmixing is proposed in this paper, which is a radial basis bilinear mixing model automatic encoder algorithm. The unsupervised autoencoder neural network method was used to solve the proportion of water pollution types by using the spectral database of water pollution sources to realize the identification function of water pollution types and determine the types of pollutant discharge enterprises. In this paper, surface water was collected as experimental samples, mixed with domestic sewage, industrial sewage, agricultural sewage, and other pollution sources, and simulated experiments were carried out to estimate the type and proportion of water pollution. Experimental results show that the detection accuracy of the proposed algorithm is significantly improved compared with the traditional algorithm. Among them, the accuracy of judging whether there is industrial sewage in the mixed experiment of three types of pollution is as high as 95.2%. This method provides an important basis for pollution source investigation and accountability.

Human settlement density, not late Holocene climate change, influenced Artiodactyla species abundance in northeastern California faunal assemblages

Variation in late Holocene artiodactyl (e.g., deer, pronghorn, bighorn sheep) hunting in northern California has often been examined from a behavioral ecological perspective to understand past foraging and land-use practices and related changes in human behavior, including settlement patterns, technological change, social signaling, large-scale resource intensification, and anthropogenic resource depression. However, rarely are past climate records and proxies of human population density coupled with zooarchaeological estimates of artiodactyl abundance to evaluate the ecological and anthropogenic drivers of changes in species representation over time. To better understand changes in human behavior related to past large game hunting, we disentangle the causal relationships between late Holocene climate change, human demography, and artiodactyl abundance to assess whether climate change, human hunting, or both impacted the abundance of artiodactyls in zooarchaeological assemblages from northeastern California. We evaluate how climatic variability and inferred human settlement density impacted artiodactyl abundance using modeled paleoclimatic reconstructions, distributions of radiocarbon dates, and faunal data derived from 35 archaeological sites and 37,319 individual faunal specimens. Using piecewise structural equation models, we assess the direct and mediating effects between climate, human settlement density, and artiodactyl abundance and determine the individual effects of these variables on large game species representation in zooarchaeological assemblages. We find that expanding human settlement density and related increases in logistical foraging—not late Holocene climate change—directly impacts the relative abundance of artiodactyls in these assemblages. Moreover, our findings reveal that the effects of climate change are entirely mediated through human settlement density. While our study is unable to decipher if observed changes in human behavior were motivated by goals related to energetic maximization or costly signaling, our study does provide a useful framework for separating the effects of human- and climate-induced explanations for variation in species composition in faunal assemblages.

Improving phytoplankton abundance estimation accuracy for autonomous microscopic imaging systems

A novel method to accurately estimate phytoplankton abundance is proposed for an autonomous microscopic imaging system (AMIS) herein. To this end, a fast fluorescence detection module is developed and added to an imaging in-flow cytometer to record the fluorescence and side-scattered signals of individual phytoplankton particles, including of those that cannot be photographed by the AMIS. Image information and the coupling relationship between the fluorescence and side-scattered signals are used to accurately detect and estimate the phytoplankton counts in water samples. The performance of the proposed estimation method is evaluated on water samples containing Alexandrium tamarense, Chattonella marina, and Scrippsiella trochoidea. The abundance estimation accuracies for these species are found to be better than 95%, 97%, and 93%, respectively, when compared to results obtained using counting chambers. The performance of the method is further evaluated by mixing the collected data of the three phytoplankton species and classifying them based on fluorescence and side-scattered signals only, assuming that these species are included in the image data but not photographed individually. The overall estimation accuracy based on this complex matrix of the three species is found to be 95.3%. These results demonstrate the suitability and practicality of the proposed method for accurately evaluating phytoplankton abundance in water. The algorithm used in this study can be a reference for other imaging in-flow cytometers.

The presence of native aromatic species in understorey plant communities predicts reduced infestation by olive fruit flies in olive orchards on Lesvos Island

AbstractThe olive fruit fly (Bactrocera oleae) (Rossi) is the most economically important insect pest in many olive cultivation areas worldwide. However, levels of infestation by this pest show remarkable variability, even among orchards in close proximity to one another. While the factors driving this variability remain uncertain, there is evidence that the presence of native plants species can influence pest populations in agro‐ecosystems via various mechanisms, suggesting that variation in the composition of understorey plant communities might plausibly play a role. In this study, we first used field trapping and plant community surveys to explore the effect of the native understorey plants Cistus creticus (Cistaceae), Lavandula stoechas (Lamiaceae), Origanum onites (Lamiaceae) and Sarcopoterium spinosum (Rosaceae) on the abundance of B. oleae across 40 olive orchards on Lesvos Island (Greece). These four plant species are widely spread in many olive orchards. Our results revealed a relationship between the plant community and the intensity of flies captured in McPhail traps, and identified the plant species C. creticus and S. spinosum whose presence was negatively correlated with fly abundance (estimate = −0.047, −0.091, respectively). The subsequent laboratory behavioural experiments revealed that exposure to olfactory cues from C. creticus and S. spinosum reduced fly attraction to odours from the olive host (Olea europaea) by 10%. These results thus reveal a relationship between the infestation levels by B. oleae and the composition of the plant community in olive orchards on Lesvos and suggest a plausible mechanism via which olfactory cues from native aromatic species might influence fly recruitment. More generally, these findings highlight the potentially important role of understorey communities in mediating resistance to B. oleae and other agricultural pests.

Future-proofing environmental DNA and trait-based predictions of food webs

Abstract Food webs represent trophic interactions within ecosystems. Matching traits of consumers and resources helps infer trophic interactions and food-web properties. Environmental (e)DNA, commonly used for detecting species occurrences, is rarely used in trait-matching studies because abundance estimates and descriptions of relevant traits are generally missing. We synthesized recent literature on inferences of trophic interactions with eDNA and trait matching to identify challenges and opportunities for coupled eDNA–trait recording schemes. Our case study shows how coupling eDNA and trait data collection improves the ability to characterize greater numbers of food webs across multiple scales ranging from spatiotemporal to trait variation. Future-proofing eDNA data sets requires the collection of new traits or the compilation of existing trait data at spatiotemporal scales that are relevant to detect current and future changes in food webs and ecosystems.

Highly asymmetric probability distribution from a finite-width upward step during inflation

We study a single-field inflation model in which the inflaton potential has an upward step between two slow-roll regimes by taking into account the finite width of the step. We calculate the probability distribution function (PDF) of the curvature perturbation P[ℛ] using the δN formalism. The PDF has an exponential-tail only for positive ℛ whose slope depends on the step width. We find that the tail may have a significant impact on the estimation of the primordial black hole abundance. We also show that the PDF P[ℛ] becomes highly asymmetric on a particular scale exiting the horizon before the step, at which the curvature power spectrum has a dip. This asymmetric PDF may leave an interesting signature in the large scale structure such as voids.

Estimation of returning Atlantic salmon stock from rod exploitation rate for principal salmon rivers in England & Wales

Abstract For effective fishery management, estimated stock sizes, along with their uncertainties, should be accurate, precise, and unbiased. Atlantic salmon Salmo salar stock assessment in England and Wales (and elsewhere across the Atlantic) estimate returning salmon stocks by applying a measure of rod exploitation rate (RER), derived from less abundant fishery-independent stock estimates, to abundant fishery-dependent data. Currently, RER estimates are generated for individual principal salmon rivers based on available local data and assumptions. We propose a single, consistent, transparent, and statistically robust method to estimate salmon stocks that transfers strength of information from “data-rich” rivers, i.e. those with fisheries-independent data, to “data-poor” rivers without such data. We proposed, fitted, simplified, and then validated a Beta–Binomial model of RER, including covariates representing angler and fish behaviours, river flow, and random effects to control for nuisance effects. Our “best” model revealed covariate effects in line with our hypotheses and generalized to data not used to train it. We used this model to extrapolate stock estimates from 12 data-rich to 52 data-poor rivers, together with their uncertainties. The resulting river-specific salmon stock estimates were judged to be useful and can be used as key inputs to river-specific, national, and international salmon stock assessments.

Target strength measurements of individual sub-Arctic krill have frequency-dependent differences from scattering model predictions.

Target strength (TS) is commonly used to convert acoustic backscatter from marine organisms to numerical abundance estimates. Shipboard, tank-based TS measurements were made on four sub-Arctic krill species (Euphausia pacifica, Thysanoessa spinifera, Thysanoessa inermis, and Thysanoessa raschii) from the eastern Bering Sea and Gulf of Alaska at discrete frequencies between 42 and 455 kHz. These measurements were compared to scattering model predictions parameterized with data from the same (when possible) individual krill. Statistically significant differences between modeled and experimental estimates at 42, 45, 120, and 131 kHz exceeded 2 dB on average. Variability in the signal-to-noise ratio, animal length, and measurements from two separate narrowband and broadband transducer pairs (at those frequencies) did not account for these differences. Scattering predictions at 120 and 131 kHz were consistent with the expected transition from Rayleigh-to-geometric scattering where models become increasingly sensitive to orientation and body shape variability. Disagreement between modeled and measured TS may be due to using scattering models developed for, and validated on, larger krill (i.e., Euphausia superba) rather than smaller species of krill. Acoustic surveys of smaller (15-30 mm) krill may require further validation of both the generalizability and parameterization of applied scattering models.

Deciphering the evolvement of microbial communities from hydrothermal vent sediments in a global change perspective

Microbial communities first respond to changes of external environmental conditions. Observing the microbial responses to environmental changes in terms of taxonomic and functional biodiversity is therefore of great interest, particularly in extreme environments, where the already extreme conditions can become even harsher. In this study, sediment samples from three different shallow hydrothermal vents in Levante Bay (Vulcano Island, Aeolian Islands, Italy) were used to set up microcosm experiments with the aim to explore the microbial dynamics under changing conditions of pH and redox potential over a 90-days period. The leading hypothesis was to establish under microcosm conditions whether the starting microbial communities of the sediments evolved differently depending on their origin. To profile the dynamics of microbial populations over time, biodiversity, enzymatic profile, total cell abundance estimations, total/respiring cell ratio were estimated by using different approaches. An evident change in the microbial community structure was observed, mainly in the microcosm containing the sediment from the most acidified site, which was characterized by a highly diversified microbial community (in prevalence composed of Thermotoga, Desulfobacterota, Planctomycetota, Synergistota and Deferribacterota). An increase in microbial resistant forms (e.g., spore-forming species) with anaerobic metabolism was detected in all experimental conditions. Differential physiological responses characterized the sedimentary microbial communities. Proteolytic activity appeared to be stimulated under microcosm conditions, whereas the alkaline phosphatase activity was significantly depressed at low pH values, like those that were measured at the station showing intermediate pH-conditions. The results confirmed a differential response of microbial communities depending on the starting environmental conditions.

Comparing abundance estimates of a cryptic carnivore in southern Patagonia using two experimental methods

AbstractDetermining the abundance of cryptic carnivores is central to building successful conservation management to mitigate conflicts and support coexistence strategies. For these reasons, there is considerable investment in developing reliable, cost‐effective tools for estimating the abundance of wildlife. Nevertheless, field‐based comparisons of abundance methods remain uncommon, even while essential to refining methods and coming to consensus around best practices. Here, we compare two approaches still being tested in real‐world application for an emblematic puma (Puma concolor) population in the Torres del Paine UNESCO Biosphere Reserve in southern Chile: (1) the unmarked estimator, space‐to‐event model (STE), which utilizes photographs gathered with camera traps, and (2) the genotype spatial partial identity model (gSPIM), which is an adaptation of the more established spatially explicit genetic capture‐recapture method (SECR) based on genetic data extracted from scats collected in systematic surveys. We show the tremendous variation in resulting STE estimates depending upon the start time of the analysis and length of the sampling window, and showcase a refined iterative sampling approach in a Bayesian framework to both utilize the full camera data and to stabilize density estimates for a given sampling window. Across all sampling, estimates from the STE model ranged from 3.19 (1.6–5.1 representing 10th and 90th percentile of credible intervals) to 7.38 (3.3–11.6) independent pumas 100 km−2. By comparison, our gSPIM model estimated 5.1 independent pumas 100 km−2 (excluding kittens) (with credible intervals of 2.2–10.3). Neither method was compared with any known density to determine their accuracy. Nevertheless, we provide initial density estimates to guide conservation strategies for wildlife agencies and local communities overseeing and hosting nascent puma tourism and livestock ranching, as well as guidelines for the use of these methods for any wildlife species.

Estimations of Elemental Abundances during Solar Flares Observed in Soft X-Rays by the MinXSS-1 CubeSat Mission

Solar flares are complex phenomena emitting all types of electromagnetic radiation and accelerating particles on timescales of minutes, converting magnetic energy to thermal, radiative, and kinetic energy through magnetic reconnections. As a result, local plasma can be heated to temperatures in excess of 20 MK. During the soft X-ray (SXR) solar flare peak, the elemental abundance of low first ionization potential elements are typically observed to be depleted from coronal values. We explored the abundance variations using disk-integrated solar spectra from the Miniature X-ray Solar Spectrometer CubeSat-1 (MinXSS-1). MinXSS-1 is sensitive to the 1–12 keV energy range with an effective 0.25 keV FWHM resolution at 5.9 keV. During the year-long mission of MinXSS-1, between 2016 May and 2017 May, 21 flares with intermittent data downlinks were observed ranging from C to M class. We examine the time evolution of temperature, volume emission measure, and elemental abundances of Fe, Ca, Si, S, and Ar with CHIANTI spectral models near the peak SXR emission times observed in the MinXSS-1 data. We determined the average absolute abundance of A(Fe) = 7.81, A(Ca) = 6.84, A(S) = 7.28, A(Si) = 7.90, and A(Ar) = 6.56. These abundances are depleted from coronal values during the SXR peak compared to nonflaring times. The elemental abundance values that are depleted from their coronal values are consistent with the process of chromospheric evaporation, in which the lower atmospheric plasma fills the coronal loops.

Comparing methods to estimate feral burro abundance

AbstractObtaining precise and unbiased estimates of feral burro (Equus asinus) abundance in the western United States is challenging due to their cryptic pelage and the rugged terrain they inhabit. Management agencies employ helicopter‐based, simultaneous double‐observer sightability surveys (hereafter denoted as DOS) to estimate abundance of burros; but the DOS method routinely produces negatively biased estimates due to residual heterogeneity in detection probability. Consequently, testing alternative methods to improve upon current procedures is warranted. Residual heterogeneity in DOS surveys can be minimized by including radio‐collared individuals in the population. Alternatively, if distance measurements are recorded, residual heterogeneity can also be reduced via a mark‐recapture distance sampling (MRDS) approach. Aerial infrared (IR) surveys offer a safer alternative than helicopter‐based surveys because they can be flown at a higher altitude and require fewer observers in the aircraft. Further, IR surveys using a distance sampling approach have been shown to generate accurate and precise estimates of feral horse (E. caballus) populations. Accordingly, we compared results of surveys using aerial IR distance sampling, the standard DOS survey, a DOS survey incorporating detections of radio‐collared individuals, and an MRDS analysis of a feral burro population with a known minimum population size in central Utah, winter 2015–2016 and spring 2016. The minimum number of burros known alive during the winter and spring surveys were 236 and 136, respectively. The average detection probability of IR surveys was P = 0.88 (SE = 0.16) and distance models produced estimates of 127 burros (95% CIs = 99–175) for the winter survey, and 94 burros (CIs = 72–134) for the spring survey. Mean detection probability of the standard DOS surveys was P = 0.78 (SE = 0.09), and model‐generated abundance estimates were 155 burros (CIs = 133–227) in winter, and 92 burros (CIs = 79–139) in spring. Incorporating detections of radio‐collared individuals in the DOS survey resulted in a decreased detection probability (P = 0.46; SE = 0.06) and increased abundance estimates to 267 (CIs = 169–571) and 155 (CIs = 128–263) for winter and spring, respectively. Mark‐recapture distance sampling produced a mean detection probability of P = 0.48 (SE = 0.12) and resulted in estimates of 282 (CIs = 178–385) and 169 (CIs = 73–310) burros in winter and spring, respectively. Our study demonstrated that aerial IR surveys conducted using standard distance sampling can produce precise estimates of burro population sizes; however, estimates were negatively biased relative to the known population size. Small sample size limits generalization of our results, but the IR‐based distance approach did not improve upon DOS surveys. Accounting for residual heterogeneity through use of radio‐collars and mark‐recapture distance sampling eliminated the negative bias from the standard DOS survey but decreased survey precision. Managers will need to decide whether unbiased but less precise abundance estimates are preferable compared to a more precise, but biased, estimate.

Comparing contemporary models to traditional indices to estimate abundance of desert bighorn sheep

AbstractAerial surveys for large ungulates produce count data that often underrepresent the number of animals. Errors in count data can lead to erroneous estimates of abundance if they are not addressed. Our objective was to address imperfect detection probability by developing a framework that produces realistic and defensible estimates of bighorn sheep (Ovis canadensis) abundance. We applied our framework to a population of desert bighorn sheep (O. c. nelsoni) in the Great Basin, Nevada, USA. We captured and marked 24 desert bighorn sheep with global positioning system (GPS)‐collars and then conducted helicopter surveys naïve to the locations of collared animals. We developed a Bayesian integrated data model to leverage information from telemetry data, helicopter survey counts, and habitat characteristics to estimate abundance while accounting for availability and perception probability (i.e., detection given availability). Distance to ridgeline, terrain ruggedness, tree cover, and slope influenced perception probability of sheep given they were viewable from the helicopter. There was also annual variation in perception probability (2018: median = 0.64, credible interval [CrI] = 0.37–0.87; 2019: median = 0.81, CrI = 0.49–0.97). The abundance estimates from the integrated data model decreased from 2018 (594; 95% CrI = 537–656) to 2019 (487; 95% CrI = 436–551). In addition, accounting for availability and imperfect perception resulted in greater estimates of abundance compared to traditional directed search methods, which were 340 for 2018 and 320 for 2019. Our modeling framework can be used to generate more defensible population estimates of bighorn sheep and other large mammals that have been surveyed in a similar manner.

Hydrogen and Dark Oxygen drive Microbial Productivity in diverse Groundwater Ecosystems

Around 50% of humankind relies on groundwater as a source of drinking water. We investigated the age, geochemistry, and microbiology of 138 groundwater samples from 87 monitoring wells (<250 m depth) located in 14 aquifers in Canada (Fig. 1). Geochemistry and microbiology showed consistent trends suggesting large-scale aerobic and anaerobic hydrogen, methane, nitrogen, and sulfur cycling carried out by diverse microbial communities. Older groundwaters, especially in aquifers with organic carbon-rich strata, contained on average more cells than younger groundwaters, challenging current estimates of subsurface cell abundances. We observed substantial concentrations of dissolved oxygen in older groundwaters that could support aerobic lifestyles in subsurface ecosystems at an unprecedented scale. Metagenomics, oxygen isotope analyses and mixing models indicated that “dark oxygen” was produced in situ via microbial dismutation. We show that ancient groundwaters sustain productive communities and highlight an overlooked oxygen source in present and past subsurface ecosystems of Earth Ruff et al. 2023). Title, Abstract, and Figure 1 are reproduced from (Ruff et al. 2023) without adaptations, according to the terms of http://creativecommons.org/licenses/by/4.0/.