Estimate Detection Probability Research Articles

Diurnal versus nocturnal surveys for foothill yellow‐legged frogs

AbstractFoothill yellow‐legged frogs (Rana boylii) are a declining species, and methodologies for assessing population occupancy have been associated with only diurnal work on the species. Diurnal visual encounter surveys are typically used to determine presence within suitable habitat; however, studies of ecologically similar species indicate a potential advantage of nocturnal surveys. At 5 sites in 4 counties in California, USA, we compared diurnal and nocturnal surveys (n = 53 paired surveys) for foothill yellow‐legged frogs, conducted 2016‐2023, to determine the value of each survey period. Generally, occupancy probabilities increased 1–22 times, detection probabilities 1–69 times, and estimated abundances 3–12 times during nocturnal versus diurnal surveys. Associated standard errors were also lower in nocturnal versus diurnal surveys. However, we noted 2 locations where diurnal surveys yielded higher detection probability or higher estimates densities compared to nocturnal surveys. We suggest that both diurnal and nocturnal surveys be required when assessing occupancy of foothill yellow‐legged frogs.

European eel (Anguilla anguilla) survival modeling based on a 22-year capture-mark-recapture survey of a Mediterranean subpopulation.

Since the 1980s, the European eel (Anguilla anguilla) has declined by over 90% in recruitment across its European and North African distribution area. This diadromous fish spawns at sea and migrates into continental waters, where it grows for three to more than 30 years, depending on habitat conditions and location. During their growth, different habitat use tactics can locally influence the life-history traits of eels, including their survival rates. Thus, the spatio-temporal dimension of this species is crucial for management. Based on a rare Mediterranean long-term survey of more than 20 years (2001-2022) in an artificial drainage canal connected to a vast brackish lagoon (the Vaccarès lagoon), we aimed to study the dynamics of one subpopulation's life-history traits. We used Bayesian multistate capture-mark-recapture (CMR) models to assess the temporal variability in survival and abundance at both seasonal and inter-annual scales, considering life-stage structure. High survival rates and low detection probabilities were found for the undifferentiated and female yellow stages. In contrast, female silver eels exhibited lower survival rates and higher capture probabilities. Estimating detection probabilities and survival rates enabled accurate assessment of relative abundance across different life stages and time periods. Our findings indicated a substantial decrease in the abundance of undifferentiated and female yellow eels in the early 2000s, whereas the abundance of female silver eels remained consistently low yet stable throughout the study period. Considering the life stage seemed essential to study the dynamics of the eel during its continental growing period. The present results will provide key elements to propose and implement suitable sustainable environmental management strategies for eel conservation.

A new double observer‐based census framework to improve abundance estimations in mountain ungulates and other gregarious species with a reduced effort

Abstract Estimating animal abundance has a key role to play in ecology and conservation, but survey methods are always challenged by imperfect detection. Among the techniques applied to deal with this issue, Double Observer (DO) is increasing in popularity due to its cost‐effectiveness. However, the effort of using DO for surveying large territories can be significant. A DO‐based survey method that allows accurate abundance estimations with reduced effort would increase the applicability of the method. This would have positive effects on the conservation of species which are challenging to survey such as mountain ungulates. We used computer simulations based on real data and a field test to assess the reliability of the DO and of a new proposed survey procedure, the Double Observer Adjusted Survey (DOAS). DOAS is based on total block counts adjusted with some DO surveys conducted in a proportion of the total area only. Such DO surveys are then used to estimate detection probability with a mark‐recapture‐derived approach. We found that full DO is much more accurate than simple block counts for abundance estimations. DOAS is a less demanding alternative to full DO and can produce comparable abundance estimates, at the cost of a slightly lower precision. However, in the DOAS overall detectability has to be estimated within a sufficient number of sites (around a quarter of the total) to obtain a higher precision and avoid large overestimations. Practical implications. DO methods could increase the reliability of abundance estimations in mountain ungulates and other gregarious species. Full DO in particular could allow researchers to obtain unbiased estimations with high precision and its usage is therefore suggested instead of block counts in wildlife monitoring. Given the high costs of full DO, the DOAS procedure could be a viable and cost‐effective survey strategy to improve abundance estimates when resources are scarce.

Importance of accounting for imperfect detection of plants in the estimation of population growth rates

Detection of plant individuals is imperfect. Not accounting for this issue can result in biased estimates of demographic parameters as important as population growth rates. In mobile organisms, a common practice is to explicitly account for detection probability during the estimation of most demographic parameters, but no study in plant populations has examined the consequences of ignoring imperfect detectability on the estimation of population growth rates. The lack of accounting for detection probability occurs because plant demographers have frequently assumed that detection is perfect, and because there is a scarcity of studies that formally compare the performance of estimation methods that incorporate detection probabilities with respect to methods that ignore detectabilities. Based on field data of five plant species and data simulations, we compared the performance of three methods that estimate population growth rates, two that do not estimate detection probabilities (direct counts of individuals and the minimum‐number‐alive method) and the other that explicitly accounts for detection probabilities (temporal symmetry models). Our aims were 1) to estimate detection probabilities, and 2) to evaluate the performance of these three methods by calculating bias, accuracy, and precision in their estimates of population growth rates. Our five plant species had imperfect detection. Estimates of population growth rates that explicitly incorporate detectabilities had better performance (less biased estimates, with higher accuracy and precision) than those obtained with the two methods that do not calculate detection probabilities. In these latter methods, bias increases as detection probability decreases. Our findings highlight the importance of using robust analytical methods that account for detection probability of plants during the estimation of critical demographic parameters such as population growth rates. In this way, estimates of plant population parameters will reliably indicate their actual status and quantitative trends.

Beyond counting calls: estimating detection probability for Antarctic blue whales reveals biological trends in seasonal calling

We explore the utility of estimating the density of calls of baleen whales for better understanding acoustic trends over time. We consider as a case study stereotyped ‘song’ calls of Antarctic blue whales (Balaenoptera musculus intermedia) on their Antarctic feeding grounds over the course of a year-long, continuous recording from 2014. The recording was made in the Southern Ocean from a deep-water autonomous hydrophone moored near the seafloor in the Eastern Indian sector of the Antarctic. We estimated call density seasonally via a Monte-Carlo simulation based on the passive sonar equation, and compared our estimates to seasonal estimates of detection rate, which are commonly reported in acoustic studies of Antarctic blue whales. The resulting seasonal call densities at our Antarctic site were strongly influenced by seasonally varying noise levels, which in turn yielded seasonal differences in detection range. Incorporating the seasonal estimates of detection area into our analysis revealed a pattern of call densities in accord with historic (non-acoustic) knowledge of Antarctic blue whale seasonal distribution and migrations, a pattern that differed from seasonal detection rates. Furthermore, our methods for estimating call densities produced results that were more statistically robust for comparison across sites and time and more meaningful for interpretation of biological trends compared to detection rates alone. These advantages came at the cost of a more complex analysis that accounts for the large variability in detection range of different sounds that occur in Antarctic waters, and also accounts for the performance and biases introduced by automated algorithms to detect sounds. Despite the additional analytical complexities, broader usage of call densities, instead of detection rates, has the potential to yield a standardized, statistically robust, biologically informative, global investigation of acoustic trends in baleen whale sounds recorded on single hydrophones, especially in the remote and difficult to access Antarctic.

Identifying Pareto‐efficient eradication strategies for invasive populations

AbstractInvasive species are a major cause of biodiversity loss and are notoriously expensive and challenging to manage. We developed a decision‐analytic framework for evaluating invasive species removal strategies, given objectives of maximizing eradication probability and minimizing costs. The framework uses an existing estimation model for spatially referenced removal data—one of the most accessible types of invasive species data—to obtain estimates of population growth rate, movement probability, and detection probability. We use these estimates in simulations to identify Pareto‐efficient strategies—strategies where increases in eradication probability cannot be obtained without increases in cost—from a set of proposed strategies. We applied the framework post hoc to a successful eradication of veiled chameleons (Chamaeleo calyptratus) and identified the potential for substantial improvements in efficiency. Our approach provides managers and policymakers with tools to identify cost‐effective strategies for a range of invasive species using only prior knowledge or data from initial physical removals.

Exploring Probability of Detection (POD) Analysis in Nondestructive Testing: A Comprehensive Review and Potential Applications in Phased Array Ultrasonic Corrosion Mapping

In nondestructive testing (NDT), ensuring defect detection, measurement accuracy, and reliability guarantees various components’ structural integrity and safety. The Probability of Detection (POD) concept has emerged as a fundamental measure of the effectiveness of an inspection technique in identifying defects. Since NDT plays a crucial role in aerospace, manufacturing, and infrastructure industries, enhancing POD has become critical. POD refers to the likelihood that a flaw or defect of a certain size will be detected using the NDT technique. The “â versus a” and the “hit/miss” methods are particularly notable among the commonly employed POD estimation methods. The POD curve is determined based on crack size measurements in the “â versus a” approach, typically used in ultrasonic testing. On the other hand, the “hit/miss” method establishes the POD curve by analysing binary outcomes, where a “hit” signifies successful detection and a “miss” denotes detection failure. This review focuses on POD in the context of NDT, specifically in phased array ultrasonic corrosion mapping (PAUCM), to uncover current uncertainty parameters and explore an innovative avenue for enhancing POD assessment by incorporating the material surface temperature as an additional parameter.

A framework for modeling the impacts of adaptive search intensity on the efficiency of abundance surveys.

When planning abundance surveys, the impact of search intensity on the quality of the density estimates is rarely considered. We constructed a time-budget modeling framework for abundance surveys using principles from optimal foraging theory. We link search intensity to the number of sample units surveyed, searcher detection probability, the number of detections made, and the precision of the estimated population density. This framework allowed us to determine how a searcher should behave to produce optimized density estimates. Using data collected from quadrat and removal surveys of zebra mussels (Dreissena polymorpha) in central Minnesota, we applied this framework to evaluate potential improvements. We found that by tuning searcher behavior, density estimates from removal surveys of zebra mussels could be improved by up to 60% in some cases, without changing the overall survey time. Our framework also predicts a critical population density where the best survey method switches from removal surveys at low densities to quadrat surveys at high densities, consistent with past empirical work. In addition, we provide simulation tools to apply this form of analysis to a number of other commonly used survey designs. Our results provide insights into how to improve the performance of many survey methods in high-density environments by either tuning searcher behavior or decoupling the estimation of population density and detection probability.

Response of dholes to prey availability and human disturbance in space and time in Southern India

Understanding spatial and temporal behavior of large carnivores is critical to developing conservation strategies that mitigate the limiting factors of prey availability and human disturbance. Dholes (Cuon alpinus) are endangered, pack-living canids persisting in tropical forests of Asia, yet significant knowledge gaps remain about their basic ecology. We estimated spatial occurrence and temporal activity of dholes relative to prey availability, anthropogenic disturbance, and landscape features using camera traps in two protected areas in Southern India. Estimated detection probability of dholes was 0.14 (95 % CI: 0.11, 0.18), while estimated occupancy probability was 0.33 (95 % CI: 0.26, 0.40). Prey availability was the strongest driver of spatial occurrence of dholes, followed by multiple measures of human disturbance. Dholes responded to human activity and human infrastructure differently in space and time, which appeared to free them to overlap with their primary prey. Dholes avoided roads spatially, avoided livestock in space and time, and avoided human activity temporally. Dholes exhibited high temporal overlap with chital, barking deer, and wild pig activity, which are likely important prey. We recommend regulating livestock presence within protected areas and limiting new road development within habitat occupied by endangered species. A proposed reservoir project to create drinking water and electricity would inundate important forested habitat for dholes along the River Cauvery where occupancy was high. This removal of habitat would significantly impact dhole presence in this landscape. Our findings advance understanding of behavioral responses by an understudied, endangered large carnivore to its primary limiting factors: prey and human disturbance.

Enhancing bird conservation in tropical urban parks through land sparing and sharing strategies: Evidence from occupancy data

Urban green spaces such as parks, play a vital role in relieving pressure on urban biodiversity. In Southeast Asia, urban park management often prioritises aesthetic appeal over urban biodiversity conservation. Management of wildlife habitat at the stand and landscape scales is necessary to support land-sharing and land-sparing conservation strategies in urban environments. To date, few studies have looked at the occurrence of urban birds in the context of land sharing and sparing strategies. We investigated how resident and migratory birds utilise urban parks based on stand-level habitat characteristics and landscape metrics. We conducted point count surveys at 49 points to estimate site occupancy and detection probability in 40 parks within highly urbanised Klang Valley, Peninsular Malaysia. Out of 90 species recorded, 14 species had more than 50 % site occupancy. The abundance of palm trees, percentage of shrub, and height of ground vegetation and woody trees positively influenced the occupancy of Black-naped Oriole, Javan Myna, House Crow, Oriental Magpie-Robin, and Yellow-vented Bulbul. While the number of woody trees and elevation negatively influenced the occupancy of Asian Glossy Starling, Spotted Dove, Zebra Dove, and Common Myna. Our findings can contribute to the effective management of urban parks, considering both stand and landscape-level characteristics to support urban biodiversity, ultimately benefiting both resident and migratory bird populations. Our research emphasises the significance of implementing both land-sparing and land-sharing strategies in urban park management. By doing so, we can promote greater avian biodiversity, preserve diverse habitats for birds, and establish crucial ecological corridors within urban landscapes.

Evaluation of the detectability of flaws in a two layer structure: A simulation-based PoD study incorporating correlated variables

Probability of Detection (PoD) models, in general, take into consideration one or multiple flaw parameters such as its length, maximum depth, and/or maximum surface area, and one flaw signal. However, due to correlation between the response signals, it might be necessary to consider multiple flaw response signals simultaneously. Hence, in this work, we demonstrate the possibility of including multiple correlated flaw signals, features, towards the construction of a PoD curve. The flaw features considered are the 3 components of the magnetic flux density. This is a simulation based PoD estimation for a narrow opening notch type flaw located in the sub-surface of a two-layer geometry. The inspection is carried out by an uniform eddy current probe that induces a spatially uniform fields into the conducting space, around the region of interest. The analysis was performed using the semi-analytical boundary element method (BEM).

Extended target trajectory Poisson multi-Bernoulli mixture filters with unknown detection probability

In most multi-extended target tracking scenarios, the target detection probability is usually unknown and time-varying, which leads to biased estimation of the state and cardinality of extended targets in online filtering. In addressing the challenge, this paper presents the unknown detection probability extended target trajectory Poisson multi-Bernoulli mixture (U-TPMBM) filter. Compared to the existing extended target Poisson multi-Bernoulli Mixture (PMBM) filter, the U-TPMBM is firstly based on sets of trajectories, which allows for direct output of target trajectory and can lead to improved trajectory estimation performance. Besides, the U-TPMBM filter integrates the unknown detection probability with the target trajectory state and thus obtains the augmented state space. By recursively estimating the augmented states via multi-target filtering approaches, it successfully realizes online and joint estimates of the unknown detection probability and the target trajectory. Finally, the U-TPMBM filter is implemented by the Beta-Gamma Gaussian Inverse Wishart (BGGIW) mixture method, especially the BGGIW-TPMBM filter. The Beta distribution is utilized to propagate densities of the unknown detection probability and the GGIW distribution to propagate densities of the target trajectory. Based on the BGGIW distribution, the trackers's recursive and closed solutions are derived in detail. The simulation experiments demonstrate that the BGGIW-TPMBM proposed in this paper can achieve robust tracking performance, even when dealing with unknown detection probabilities.

Influence of temporary emigration on wood turtle (Glyptemys insculpta) detectability, with implications for abundance estimation.

Reliable population estimates are important for making informed management decisions about wildlife species. Standardized survey protocols have been developed for monitoring population trends of the wood turtle (Glyptemys insculpta), a semi-aquatic freshwater turtle species of conservation concern throughout its distribution in east-central North America. The protocols use repeated active search surveys of defined areas, allowing for estimation of survey-specific detection probability (p) and site-specific abundance. These protocols assume population closure within the survey area during the survey period, which is unlikely to be met as wood turtles are a highly mobile species. Additionally, current protocols use a single-pass design that does not allow for separation of availability (pa) and detectability (pd). If there are systematic influences on pa or pd that are not accounted for in the survey design or data analysis, then resulting abundance estimates could be biased. The objectives of this study were to determine if pa is a random process and if pa and pd are influenced by demographic characteristics. We modified the wood turtle survey protocol used in the upper Midwest to include a double-pass design, allowing us to estimate pa and pd using a robust design capture-recapture model. The modified protocol was implemented at 14 wood turtle monitoring sites in Minnesota and Wisconsin between 2017 and 2022. Our results indicated that pa was non-random and that pd increased with turtle carapace length. Our study suggests that model assumptions for current wood turtle population models may be violated, likely resulting in an overestimation of abundance. We discuss possible protocol and modeling modifications that could result in more accurate wood turtle abundance estimates.

Evaluation of drone surveys for ungulates in southwestern rangelands

AbstractDrone platforms are increasingly used for aerial wildlife surveys, but the validity of population counts has not been fully evaluated in all environments. Aerial surveys generally undercount the true population size and one must estimate detection probability (p) to correct for missed individuals. Detection probability for visual observers is influenced by vegetation and terrain characteristics, but the use of thermal cameras as the observer may also introduce additional factors influencing detection probability. We conducted diurnal, thermal‐based drone surveys for ungulates during February–April 2020 in South Texas, USA, on sites with varying degrees of woody cover and terrain. We examined histograms of georeferenced perpendicular distances to determine the effect of habitat on detection probabilities. We also examined precision in population estimates and variation in repeated surveys. Finally, we compared drone population estimates to independent estimates derived from helicopter, spotlight, and trail‐camera surveys. Distributions of perpendicular distances from the transect were affected by habitat characteristics. A flat grassland site had relatively few detections near the transect because thermal (solar) reflectance in the center of the footage obscured detections. A hilly brushy site had a uniform p (1.00) but resulted in a severe undercount due to the inability of the drone to follow contours of hills. The flat brushy site had a lower p (0.63), indicating visibility bias. Two additional flat, brushy sites were surveyed repeatedly (n = 5 and 9 surveys, respectively). All combinations of up to 3 repeated surveys were pooled to meet the recommended minimum number of detections for distance sampling analyses (≥60 detections). Population estimates had acceptable precision (CV ≤ 20%) 80.7% of the time and variation among repeated surveys was acceptable (CV = 9% and 23%, respectively). Drone‐based population estimates were comparable with estimates generated from corrected helicopter, spotlight, and trail‐camera surveys. Overall, diurnal drone surveys can generate population estimates for large ungulates on southwestern rangelands after accounting for visibility bias, but may be limited by terrain and thermal conditions.

Long-term field studies of a distributed network of sensors for environmental radiological monitoring

The W-MON project goal is to establish an automatic control mechanism of the presence of radioactive material in conventional waste containers at CERN using a distributed network of interconnected low-power radiation sensors. This network facilitates continuous data recording, transfer and storage in a database while allowing online and offline data analysis, in addition to alarm triggering. Data transmission, processing and evaluation is achieved by a centralized IoT end-to-end data architecture that has been developed for real-time monitoring and visualization of the radiation levels in waste containers. In this paper the results of field tests of the W-MON system described in two previous papers are presented for three different types of sensors. Estimation of failure detection probability, long-term stability tests and sensitivity studies carried out using radioactive samples of various activities placed in standard waste containers are described. A comparison between the manual monitoring procedure currently used at CERN and the W-MON system is discussed in detail.

Diadromous fish run assessment: a double-observer model using acoustic cameras to correct imperfect detection and improve population abundance estimates

IntroductionDiadromous fish populations have strongly declined over decades, and many species are protected through national and international regulations. They account for less than 1% of fish biodiversity worldwide, but they are among the most perceptible linkages between freshwater and marine ecosystems. During their migration back and forth, diadromous fish species are subjected to many anthropogenic threats, among which river damming can severely limit access to vital freshwater habitats and jeopardize population sustainability. Here, we developed a method based on a double-observer modeling approach for estimating the abundance of diadromous fish during their migration in rivers.MethodsThe method relies on two independent and synchronous records of fish counts that were analyzed jointly thanks to a hierarchical Bayesian model to estimate detection efficiencies and daily fish passage. We used simulated data to test model robustness and identify conditions under which the developed approach can be used. The approach was then applied to empirical data to estimate the annual silver eel run in the Touques River, France.ResultsThe analysis of simulated datasets and the study case gives evidence that the model can provide robust,accurate, and precise estimates of detection probabilities and total fish abundance in a set of conditions dependent on the information provided in the data (annual distribution of fish passage, annual number of observation, pairing period, etc.).DiscussionThen, the method can be applied to various species and counting systems, including nomad acoustic camera devices. We discuss its relevance for programs on river continuity restoration, notably to quantify population restoration associated with dam removals.

Estimating the effort required to detect Kirtland's snakes (Clonophis kirtlandii)

AbstractSnakes are difficult to study due to their cryptic coloration, minimal movements, and use of inaccessible habitats. Although well‐timed surveys during a species' active season can result in higher detection rates and conserve survey resources (i.e., time and money), survey effort may not ensure the detection of rare and cryptic species. Thus, in such instances, a strategic species‐specific sampling design is needed. The Kirtland's snake (Clonophis kirtlandii) is a rare, cryptic species assumed to be experiencing range‐wide declines. Naturalists have noted the disappearance of Kirtland's snakes from various habitats since the early 1970s. The primary objective of our study was to determine detection of Kirtland's snakes and the environmental and temporal factors influencing detection. We calculated the effort needed to detect individuals at sites by estimating detection probabilities of 3 known Kirtland's snake populations in Illinois from 2019 to 2021. Based on 77 Kirtland's snake detections over 226 site visits (34.1%) across 3 study sites, we found that high cloud cover, moderate air temperature, and low relative humidity enhanced the detection probability of this species. The middle of May to the beginning of July was the best time to conduct surveys when detection rates were highest. As our results suggested, it is imperative to establish strategic monitoring programs maximizing conservation resources to document populations for conservation action and range shifts for species of conservation concern, such as Kirtland's snakes.

OFDM-Based Massive Connectivity for LEO Satellite Internet of Things

Low earth orbit (LEO) satellite has been considered as a potential supplement for the terrestrial Internet of Things (IoT). In this paper, we consider grant-free non-orthogonal random access (GF-NORA) in the orthogonal frequency division multiplexing (OFDM) system to increase access capacity and reduce access latency for LEO satellite-IoT. We focus on the joint device activity detection (DAD) and channel estimation (CE) problem at the satellite access point. The delay and the Doppler effect of the LEO satellite channel are assumed to be partially compensated. We propose an OFDM-symbol repetition technique to better distinguish the residual Doppler frequency shifts, and present a grid-based parametric probability model to characterize channel sparsity in the delay-Doppler-user domain, as well as to characterize the relationship between the channel states and the device activity. Based on that, we develop a robust Bay esian message-passing algorithm named modified variance state propagation (MVSP) for joint DAD and CE. Moreover, to tackle the mismatch between the real channel and its on-grid representation, an expectation–maximization (EM) framework is proposed to learn the grid parameters. Simulation results demonstrate that our proposed algorithms significantly outperform the existing approaches in both activity detection probability and channel estimation accuracy.

Occupancy of the Ethiopian endemic Moorland Francolin in pristine and degraded Afroalpine biome using a camera trap approach.

Occupancy modeling is an essential tool for understanding species-habitat associations, thereby helping to plan the conservation of rare and threatened wildlife species. The conservation status and ecology of several avian species, particularly ground-dwelling birds, are poorly known in Ethiopia. We used camera trap-based occupancy modeling to investigate habitat covariate influence on occupancy (Ψ) and detection probability (ρ) estimates of Moorland Francolins Scleroptila psilolaema from spatially replicated surveys across both relatively pristine and disturbed landscapes in the Afroalpine biome of Ethiopia. Model-averaged estimate of across all sites was 0.76 (SD = 0.28) and was 0.77 (SD = 0.13) in the pristine landscape. The of the species in the disturbed landscape was 0.56 (SD = 0.19) and was 0.48 (SD = 0.06). As hypothesized, based on our model-averaged beta coefficient estimates (βmean ± SE), predators significantly negatively influenced the occupancy of Moorland Francolins in pristine habitat. We also found a significant positive association of occupancy with herb species richness. Contrary to our prediction, distance to road significantly negatively influence the occupancy of the species, suggesting that occupancy probability was highest in proximity to roadsides and trails in the pristine habitat. There was no significant influence of habitat covariates on the occupancy of the species in the disturbed habitat. The most important covariates that significantly influence the detectability of the species in pristine habitat included sampling occasion and precipitation. The greater occupancy and detectability of this endemic species in the pristine habitat could be linked with the particular conservation status and management of this biodiversity hotspot in the central highlands of Ethiopia. Our results suggest that strict legal enforcement is required to sustainably preserve Moorland Francolins and the ecological integrity of the entire Afroalpine biome. We recommend using camera traps in order to develop realistic and effective conservation and management strategies for rare, sensitive, cryptic, and ground-dwelling animals in the region.

Matching visual and acoustic events to estimate detection probability for small cetaceans in the ACCOBAMS Survey Initiative

Estimating the detection probability of small cetaceans using either visual or acoustic surveys is difficult because they do not surface or vocalise continuously and can be imperceptible to an observer or hydrophone. Animals seen at the surface may have lower vocalisation rates, while submerged individuals may be more vocally active. This study aims to estimate visual, acoustic and combined detection probability by using Mark-Recapture Distance Sampling (MRDS) methodology. We used vessel-based visual sightings and acoustic data (based on click identification) collected simultaneously during the ACCOBAMS Survey Initiative in summer 2018 onboard theR/V Song of the Whale. This study focused on small cetaceans in the Mediterranean Sea, including the most commonly-encountered species, the striped dolphin(Stenella coeruleoalba). We identified duplicate events between visual and acoustic platforms using a decision tree based on time and distance thresholds to estimateg(0) (the detection probability on the trackline) for small cetaceans. A total of 30 duplicate events were identified from 107 and 109 events identified by the visual and acoustic platforms respectively. We tested the models with two key functions. With a hazard-rate key function, theg(0) was estimated at 0.52 (CV=21.0%) for both platforms combined, 0.29 (CV=25.6%) for the visual platform and 0.32 (CV=25.1%) for the acoustic platform. With a half-normal key function,g(0) was estimated at 0.51 (CV = 21.7%) for both platforms combined, 0.29 (CV = 25.6%) for the visual platform and 0.33 (CV = 23.2%) for the acoustic platform. Our results illustrate that passive acoustic monitoring can be used as an independent platform in MRDS to estimate the detection probability. Our estimate ofg(0) was well below 1, far from the perfect detection commonly assumed for abundance estimation. Without correction for detection biases, total abundance would be underestimated by a factor of two when using both acoustic and visual data. This highlights the importance of using dual-platform surveys to estimate detection probability in order to improve abundance estimates and conservation efforts.