Assessing conservation status with extensive but low-resolution data: Application of frequentist and Bayesian models to endangered Athabasca River rainbow trout

Use of extensive but low-resolution abundance data is common in the assessment of species at-risk status based on quantitative decline criteria under International Union for Conservation of Nature (IUCN) and national endangered species legislation. Such data can be problematic for 3 reasons. First, statistical power to reject the null hypothesis of no change is often low because of small sample size and high sampling uncertainty leading to a high frequency of type II errors. Second, range-wide assessments composed of multiple site-specific observations do not effectively weight site-specific trends into global trends. Third, uncertainty in site-specific temporal trends and relative abundance are not propagated at the appropriate spatial scale. A common result is the propensity to underestimate the magnitude of declines and therefore fail to identify the appropriate at-risk status for a species. We used 3 statistical approaches, from simple to more complex, to estimate temporal decline rates for a designatable unit (DU) of rainbow trout in the Athabasca River watershed in western Canada. This DU is considered a native species for purposes of listing because of its genetic composition characterized as >0.95 indigenous origin in the face of continuing introgressive hybridization with introduced populations in the watershed. Analysis of abundance trends from 57 time series with a fixed-effects model identified 33 sites with negative trends, but only 2 were statistically significant. By contrast, a hierarchical linear mixed model weighted by site-specific abundance provided a DU-wide decline estimate of 16.4% per year and a 3-generation decline of 93.2%. A hierarchical Bayesian mixed model yielded a similar 3-generation decline trend of 91.3% and the posterior distribution showed that the estimate had a >99% probability of exceeding thresholds for an endangered listing. We conclude that the Bayesian approach was the most useful because it provided a probabilistic statement of threshold exceedance in support of an at-risk status recommendation.

Monitoring partially marked populations using camera and telemetry data

Long-term monitoring is an important component of effective wildlife conservation. However, many methods for estimating density are too costly or difficult to implement over large spatial and temporal extents. Recently developed spatial mark-resight (SMR) models are increasingly being applied as a cost-effective method to estimate density when data include detections of both marked and unmarked individuals. We developed a generalized SMR model that can accommodate long-term camera data and auxiliary telemetry data for improved spatiotemporal inference in monitoring efforts. The model can be applied in two stages, with detection parameters estimated in the first stage using telemetry data and camera detections of instrumented individuals. Density is estimated in the second stage using camera data, with all individuals treated as unmarked. Serial correlation in detection and density parameters is accounted for using time-series models. The two-stage approach reduces computational demands and facilitates the application to large data sets from long-term monitoring initiatives. We applied the model to 3 years (2015-2017) of white-tailed deer (Odocoileus virginianus) data collected in three study areas of the Big Cypress Basin, Florida, USA. In total, 59 females marked with ear tags and fitted with GPS-telemetry collars were detected along with unmarked females on 180 remote cameras. Most of the temporal variation in density was driven by seasonal fluctuations, but one study area exhibited a slight population decline during the monitoring period. Modern technologies such as camera traps provide novel possibilities for long-term monitoring, but the resulting massive data sets, which are subject to unique sources of observation error, have posed analytical challenges. The two-stage spatial mark-resight framework provides a solution with lower computational demands than joint SMR models, allowing for easier implementation in practice. In addition, after detection parameters have been estimated, the model may be used to estimate density even if no synchronous auxiliary information on marked individuals is available, which is often the case in long-term monitoring.

A simple and viable approach to estimate population trends.. [DOI: 10.1101/2022.03.18.484446] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

Changes in population abundances over time are of central concern for environmental conservation and the understanding of population dynamics. The standard slope estimator has restricting assumptions and lacks a constant range, which makes its interpretation less intuitive. Herein, more robust measures of trend. It is based on proportional difference and can be used for data on various scale types. If it is applied to ranks it yields the correlation coefficient. Related measures of association are described that assess the relationship between species, including a rank-order correlation that is sensitive to top ranks and a correlation for continuous data that is more robust than the correlation coefficient. All proposed measures have a range between –1 and +1. Furthermore, they can provide a common ground for evaluating trend strength and strength of association for populations undergoing very different dynamics.

Review: COVID-19 highlights the importance of camera traps for wildlife conservation research and management

COVID-19 has altered many aspects of everyday life. For the scientific community, the pandemic has called upon investigators to continue work in novel ways, curtailing field and lab research. However, this unprecedented situation also offers an opportunity for researchers to optimize and further develop available field methods. Camera traps are one example of a tool used in science to answer questions about wildlife ecology, conservation, and management. Camera traps have long battery lives, lasting more than a year in certain cases, and photo storage capacity, with some models capable of wirelessly transmitting images from the field. This allows researchers to deploy cameras without having to check them for up to a year or more, making them an ideal field research tool during restrictions on in-person research activities such as COVID-19 lockdowns. As technological advances allow cameras to collect increasingly greater numbers of photos and videos, the analysis techniques for large amounts of data are evolving. Here, we describe the most common research questions suitable for camera trap studies and their importance for biodiversity conservation. As COVID-19 continues to affect how people interact with the natural environment, we discuss novel questions for which camera traps can provide insights on. We conclude by summarizing the results of a systematic review of camera trap studies, providing data on target taxa, geographic distribution, publication rate, and publication venues to help researchers planning to use camera traps in response to the current changes in human activity.

Reliability of animal counts and implications for the interpretation of trends

Population time series analysis is an integral part of conservation biology in the current context of global changes. To quantify changes in population size, wildlife counts only provide estimates because of various sources of error. When unaccounted for, such errors can obscure important ecological patterns and reduce confidence in the derived trend. In the case of highly gregarious species, which are common in the animal kingdom, the estimation of group size is an important potential bias, which is characterized by high variance among observers. In this context, it is crucial to quantify the impact of observer changes, inherent to population monitoring, on i) the minimum length of population time series required to detect significant trends and ii) the accuracy (bias and precision) of the trend estimate.We acquired group size estimation error data by an experimental protocol where 24 experienced observers conducted counting simulation tests on group sizes. We used this empirical data to simulate observations over 25 years of a declining population distributed over 100 sites. Five scenarios of changes in observer identity over time and sites were tested for each of three simulated trends (true population size evolving according to deterministic models parameterized with declines of 1.1%, 3.9% or 7.4% per year that justify respectively a "declining," "vulnerable" or "endangered" population under IUCN criteria).We found that under realistic field conditions observers detected the accurate value of the population trend in only 1.3% of the cases. Our results also show that trend estimates are similar if many observers are spatially distributed among the different sites, or if one single observer counts all sites. However, successive changes in observer identity over time lead to a clear decrease in the ability to reliably estimate a given population trend, and an increase in the number of years of monitoring required to adequately detect the trend.Minimizing temporal changes of observers improve the quality of count data and help taking appropriate management decisions and setting conservation priorities. The same occurs when increasing the number of observers spread over 100 sites. If the population surveyed is composed of few sites, then it is preferable to perform the survey by one observer. In this context, it is important to reconsider how we use estimated population trend values and potentially to scale our decisions according to the direction and duration of estimated trends, instead of setting too precise threshold values before action.

Experimenting With the Past to Improve Environmental Monitoring

Long-term monitoring programs are a fundamental part of both understanding ecological systems and informing management decisions. However, there are many constraints which might prevent monitoring programs from being designed to consider statistical power, site selection, or the full costs and benefits of monitoring. Key considerations can be incorporated into the optimal design of a management program with simulations and experiments. Here, we advocate for the expanded use of a third approach: non-random resampling of previously-collected data. This approach conducts experiments with available data to understand the consequences of different monitoring approaches. We first illustrate non-random resampling in determining the optimal length and frequency of monitoring programs to assess species trends. We then apply the approach to a pair of additional case studies, from fisheries and agriculture. Non-random resampling of previously-collected data is underutilized, but has the potential to improve monitoring programs.

Spatially Explicit Capture-Recapture Through Camera Trapping: A Review of Benchmark Analyses for Wildlife Density Estimation

Camera traps have become an important research tool for both conservation biologists and wildlife managers. Recent advances in spatially explicit capture-recapture (SECR) methods have increasingly put camera traps at the forefront of population monitoring programs. These methods allow for benchmark analysis of species density without the need for invasive fieldwork techniques. We conducted a review of SECR studies using camera traps to summarize the current focus of these investigations, as well as provide recommendations for future studies and identify areas in need of future investigation. Our analysis shows a strong bias in species preference, with a large proportion of studies focusing on large felids, many of which provide the only baseline estimates of population density for these species. Furthermore, we found that a majority of studies produced density estimates that may not be precise enough for long-term population monitoring. We recommend simulation and power analysis be conducted before initiating any particular study design and provide examples using readily available software. Furthermore, we show that precision can be increased by including a larger study area that will subsequently increase the number of individuals photo-captured. As many current studies lack the resources or manpower to accomplish such an increase in effort, we recommend that researchers incorporate new technologies such as machine-learning, web-based data entry, and online deployment management into their study design. We also cautiously recommend the potential of citizen science to help address these study design concerns. In addition, modifications in SECR model development to include species that have only a subset of individuals available for individual identification (often called mark-resight models), can extend the process of explicit density estimation through camera trapping to species not individually identifiable.

Determining optimal sampling strategies for monitoring mercury and reproductive success in common loons in the Adirondacks of New York

The common loon (Gavia immer), a top predator in the freshwater food web, has been recognized as an important bioindicator of aquatic mercury (Hg) pollution. Because capturing loons can be difficult, statistical approaches are needed to evaluate the efficiency of Hg monitoring. Using data from 1998 to 2016 collected in New York's Adirondack Park, we calculated the power to detect temporal changes in loon Hg concentrations and fledging success as a function of sampling intensity. There is a tradeoff between the number of lakes per year and the number of years needed to detect a particular rate of change. For example, a 5% year^-1 change in Hg concentration could be detected with a sampling effort of either 15 lakes per year for 10 years, or 5 lakes per year for 15 years, given two loons sampled per lake per year. A 2% year^-1 change in fledging success could be detected with a sampling effort of either 40 lakes per year for 15 years, or 30 lakes per year for 20 years. We found that more acidic lakes required greater sampling intensity than less acidic lakes for monitoring Hg concentrations but not for fledging success. Power analysis provides a means to optimize the sampling designs for monitoring loon Hg concentrations and reproductive success. This approach is applicable to other monitoring schemes where cost is an issue.

Of power and despair in cetacean conservation: estimation and detection of trend in abundance with noisy and short time-series

Many conservation instruments rely on detecting and estimating a population decline in a target species to take action. Trend estimation is difficult because of small sample size and relatively large uncertainty in abundance/density estimates of many wild populations of animals. Focusing on cetaceans, we performed a prospective analysis to estimate power, type-I, sign (type-S) and magnitude (type-M) error rates of detecting a decline in short time-series of abundance estimates with different signal-to-noise ratio. We contrasted results from both unregularized (classical) and regularized approaches. The latter allows to incorporate prior information when estimating a trend. Power to detect a statistically significant estimates was in general lower than 80%, except for large declines. The unregularized approach (status quo) had inflated type-I error rates and gave biased (either over- or under-) estimates of a trend. The regularized approach with a weakly-informative prior offered the best trade-off in terms of bias, statistical power, type-I, type-S and type-M error rates and confidence interval coverage. To facilitate timely conservation decisions, we recommend to use the regularized approach with a weakly-informative prior in the detection and estimation of trend with short and noisy time-series of abundance estimates.

What Have Long-Term Field Studies Taught Us About Population Dynamics?

Long-term studies have been crucial to the advancement of population biology, especially our understanding of population dynamics. We argue that this progress arises from three key characteristics of long-term research. First, long-term data are necessary to observe the heterogeneity that drives most population processes. Second, long-term studies often inherently lead to novel insights. Finally, long-term field studies can serve as model systems for population biology, allowing for theory and methods to be tested under well-characterized conditions. We illustrate these ideas in three long-term field systems that have made outsized contributions to our understanding of population ecology, evolution, and conservation biology. We then highlight three emerging areas to which long-term field studies are well positioned to contribute in the future: ecological forecasting, genomics, and macrosystems ecology. Overcoming the obstacles associated with maintaining long-term studies requires continued emphasis on recognizing the benefits of such studies to ensure that long-term research continues to have a substantial impact on elucidating population biology.

Detecting trends in body size: empirical and statistical requirements for intraspecific analyses

Attributing biological explanations to observed ecogeographical and ecological patterns require eliminating potential statistical and sampling artifacts as alternative explanations of the observed patterns. Here, we assess the role of sample size, statistical power, and geographic inclusivity on the general validity and statistical significance of relationships between body size and latitude for 3 well-studied species of turtles. We extend those analyses to emphasize the importance of using statistically robust data in determining macroecological patterns. We examined intraspecific trends in body size with latitude in Chelydra serpentina, Chrysemys picta, and Trachemys scripta using Pearson’s correlations, diagnostic tests for influential points, and resampling. Existing data were insufficient to ascertain a latitudinal trend in body size for C. serpentina or T. scripta. There was a significant relationship for C. picta, however, resampling analyses show that, on average, 16 of the 23 available independent populations were needed to demonstrate a significant relationship and that at least 20 of 23 populations were required to obtain a statistically powerful correlation between body size and latitude. Furthermore, restricting the latitudes of populations resampled shows that body size trends of C. picta were largely due to leveraging effects of populations at the edge of the species range. Our results suggest that broad inferences regarding ecological trends in body size should be made with caution until underlying (intraspecific) patterns in body size can be statistically and conclusively demonstrated.

Avoiding misleading messages: Population assessment using camera trapping is not a simple task

Population assessment is indispensable for appropriate and socially acceptable conservation and management of wildlife populations. This article critiques the paper by Campos-Candela et al. 2018 and highlights issues that could lead to inappropriate management and conservation policies.

Population ecology and the management of whale watching operations on a data-deficient dolphin population

Whale watching is a popular commercial activity, producing socio-ecological benefits but also potential long-term effects on the targeted cetacean population. This industry is currently developing in data-deficient contexts in a largely unregulated fashion. Management schemes should adopt precaution and be informed by the relevant literature, but would be more effective if the assessment of the target population vulnerability, biological impacts, and management implications was drawn from site-specific data.This paper focuses on a reef-associated, data-deficient population of spinner dolphins in the Egyptian Red Sea. In Satayah Reef, new information on population size and dynamic parameters were documented using visual observation and photo-identification-based capture-recapture methods (Cormack-Jolly-Seber time-since-marking model).Dolphins occurred on 98% of the survey days. Average school size was 66 individuals (±42.1 SE), with most groups including calves. The population was equally divided into recurrent and transient individuals. An "emigration + mortality" model best described residence at the site. Five recurrent males (5% of the Satayah population) provided connectivity between this and the geographically close population of Samadai Reef.Average annual survival probability was 0.83 (±0.06 SE) in the year following first capture and 0.99 (±0.06 SE) for recurrent individuals. Mean yearly population sizes ranged 143-207 individuals.The study had the power to detect a 30% decline in the population, but not the rate of change in abundance estimated from the data (r = 0.018 ± 0.04), which would have required a 3- to 5-times longer study. Synthesis and application: These findings advance the assessment of the Satayah population's intrinsic vulnerability and have three major management applications: (a) the delineation of management units; (b) the identification of key indicators for future impact monitoring and assessment; and (c) realistic estimates of the statistical power for trend detection. Based on our results, we recommend supporting future research, devising site-specific time-area closure plans, and integrating them in a regional scheme. Approaches employed in this case study can inform the management of whale watching industries targeting other data-deficient populations.

The power to detect regional declines in common bird populations using continental monitoring data

Anthropogenic environmental change is driving the rapid loss of biodiversity. Large declines in the abundance of historically common species are now emerging as a major concern. Identifying declining populations through long-term biodiversity monitoring is vital for implementing timely conservation measures. It is, therefore, critical to evaluate the likelihood that persistent long-term population trends of a given size could be detected using existing monitoring data and methods. Here, we test the power to detect declines in Australia's common landbirds using long-term citizen science monitoring. We use spatially explicit simulations of occupancy dynamics and virtual sampling, designed to mimic bird monitoring in better-sampled regions of Australia, to assess likely power in these data to detect trends relevant for conservation. We predict the statistical power for 326 common species that meet minimum requirements for monitoring data across 10 regions of Australia, estimating the number of species for which we would have a high (≥80%) chance of detecting declines of different sizes. The power to detect declines of ≥30% per decade was predicted to be high for at least one-third of the common species in 7 of 10 regions, with a total of 103 (32% of 326) unique species sufficiently monitored in at least one region. These species spanned 12 taxonomic orders, four orders of magnitude in body mass, and a broad diversity of dietary guilds, suggesting the current species pool will likely serve as robust indicators for a broad range of environmental states and pressures. Power was strongly affected by species' detectability, and power to detect even large declines was negligible when species are detected on ≤50% of visits to an occupied site. Predicted power for many species fell just short of the 80% threshold in one or more regions, which suggests an increase in effort targeting these species could greatly enhance the species and regional representation of these data. Against the backdrop of unprecedented biodiversity losses, this study shows how critical evaluation of existing monitoring schemes is valuable both for assessing the contribution of citizen science schemes to biodiversity monitoring and for designing strategic monitoring to significantly improve the knowledge these schemes provide.

Baseline Alligator Nesting Data in Arthur R. Marshall Loxahatchee National Wildlife Refuge to Inform Monitoring

Monitoring key ecological attributes helps land managers understand the current state of the resource and decide if management action is necessary. Baseline data on spatial and temporal variability of attributes to be monitored is important for development of successful monitoring programs. In this study, I collected data from 2000 to 2004 on American alligator Alligator mississippiensis nesting in the Arthur R. Marshall Loxahatchee National Wildlife Refuge to determine feasibility of conducting alligator nest surveys and collect baseline data on alligator nesting status and variability. I used nest data to provide examples of potential monitoring strategies for tracking trends over time or understanding the effects of different hydrologic conditions on alligator nesting. Conducting ground surveys with airboats in Arthur R. Marshall Loxahatchee National Wildlife Refuge proved to be an effective method of finding alligator nests. Number of nests per 1.6 km × 1.6 km (256-ha) plot ranged from 1 to 12, and by year from 28 to 53. Overall, average number of nests per hour ranged from 1.8 ± 0.26 (SE) in 2000 to a low of 0.84 ± 0.08 in 2004. Using data from this study for the six plots sampled each year, and assuming no change in variability, power analysis shows that 10 y of sampling would allow for detection of an annual 10% change in number of nests per hour, with power and level of certainty set equal at 90% (β and α both 0.10). Additionally, 15 y of data would allow for a detection of a 5% change per year. Thirty-seven plots per area would be necessary to assess a 40% difference in number of alligator nests per hour in areas with different hydrologic conditions with power and level of certainty at 90%. Land managers can use these data and analyses, along with examples of monitoring strategies, to guide development of more specific monitoring protocols that address restoration objectives and management actions throughout the Florida Everglades.

Implications of survey effort on estimating demographic parameters of a long-lived marine top predator

Effective management of wildlife populations rely on knowledge of their abundance, survival, and reproductive rates. Maintaining long‐term studies capable of estimating demographic parameters for long‐lived, slow‐reproducing species is challenging. Insights into the effects of research intensity on the statistical power to estimate demographic parameters are limited. Here, we investigate implications of survey effort on estimating abundance, home range sizes, and reproductive output of Indo‐Pacific bottlenose dolphins (Tursiops aduncus), using a 3‐year subsample of a long‐term, capture–recapture study off Bunbury, Western Australia. Photo‐identification on individual dolphins was collected following Pollock's Robust Design, where seasons were defined as “primary periods”, each consisting of multiple “secondary periods.” The full dataset consisted of 12 primary periods and 72 secondary periods, resulting in the study area being surveyed 24 times/year. We simulated reduced survey effort by randomly removing one, two, or three secondary periods per primary period. Capture–recapture models were used to assess the effect of survey intensity on the power to detect trends in population abundance, while individual dolphin sighting histories were used to assess the ability to conduct home range analyses. We used sighting records of adult females and their calving histories to assess survey effort on quantifying reproductive output. A 50% reduction in survey effort resulted in (a) up to a 36% decline in population abundance at the time of detection; (b) a reduced ability to estimate home range sizes, by increasing the time for individuals to be sighted on ≥30 occasions (an often‐used metric for home range analyses) from 7.74 to 14.32 years; and (c) 33%, 24%, and 33% of annual calving events across three years going undocumented, respectively. Results clearly illustrate the importance of survey effort on the ability to assess demographic parameters with clear implications for population viability analyses, population forecasting, and conservation efforts to manage human–wildlife interactions.

Understanding meta-population trends of the Australian fur seal, with insights for adaptive monitoring

Effective ecosystem-based management requires estimates of abundance and population trends of species of interest. Trend analyses are often limited due to sparse or short-term abundance estimates for populations that can be logistically difficult to monitor over time. Therefore it is critical to assess regularly the quality of the metrics in long-term monitoring programs. For a monitoring program to provide meaningful data and remain relevant, it needs to incorporate technological improvements and the changing requirements of stakeholders, while maintaining the integrity of the data. In this paper we critically examine the monitoring program for the Australian fur seal (AFS) Arctocephalus pusillus doriferus as an example of an ad-hoc monitoring program that was co-ordinated across multiple stakeholders as a range-wide census of live pups in the Austral summers of 2002, 2007 and 2013. This 5-yearly census, combined with historic counts at individual sites, successfully tracked increasing population trends as signs of population recovery up to 2007. The 2013 census identified the first reduction in AFS pup numbers (14,248 live pups, -4.2% change per annum since 2007), however we have limited information to understand this change. We analyse the trends at breeding colonies and perform a power analysis to critically examine the reliability of those trends. We then assess the gaps in the monitoring program and discuss how we may transition this surveillance style program to an adaptive monitoring program than can evolve over time and achieve its goals. The census results are used for ecosystem-based modelling for fisheries management and emergency response planning. The ultimate goal for this program is to obtain the data we need with minimal cost, effort and impact on the fur seals. In conclusion we identify the importance of power analyses for interpreting trends, the value of regularly assessing long-term monitoring programs and proper design so that adaptive monitoring principles can be applied.

Compensating for geographic variation in detection probability with water depth improves abundance estimates of coastal marine megafauna

The probability of an aquatic animal being available for detection is typically <1. Accounting for covariates that reduce the probability of detection is important for obtaining robust estimates of the population abundance and determining its status and trends. The dugong (Dugong dugon) is a bottom-feeding marine mammal and a seagrass community specialist. We hypothesized that the probability of a dugong being available for detection is dependent on water depth and that dugongs spend more time underwater in deep-water seagrass habitats than in shallow-water seagrass habitats. We tested this hypothesis by quantifying the depth use of 28 wild dugongs fitted with GPS satellite transmitters and time-depth recorders (TDRs) at three sites with distinct seagrass depth distributions: 1) open waters supporting extensive seagrass meadows to 40 m deep (Torres Strait, 6 dugongs, 2015); 2) a protected bay (average water depth 6.8 m) with extensive shallow seagrass beds (Moreton Bay, 13 dugongs, 2011 and 2012); and 3) a mixture of lagoon, coral and seagrass habitats to 60 m deep (New Caledonia, 9 dugongs, 2013). The fitted instruments were used to measure the times the dugongs spent in the experimentally determined detection zones under various environmental conditions. The estimated probability of detection was applied to aerial survey data previously collected at each location. In general, dugongs were least available for detection in Torres Strait, and the population estimates increased 6–7 fold using depth-specific availability correction factors compared with earlier estimates that assumed homogeneous detection probability across water depth and location. Detection probabilities were higher in Moreton Bay and New Caledonia than Torres Strait because the water transparency in these two locations was much greater than in Torres Strait and the effect of correcting for depth-specific detection probability much less. The methodology has application to visual survey of coastal megafauna including surveys using Unmanned Aerial Vehicles.

The power of monitoring: optimizing survey designs to detect occupancy changes in a rare amphibian population

Biodiversity conservation requires reliable species assessments and rigorously designed surveys. However, determining the survey effort required to reliably detect population change can be challenging for rare, cryptic and elusive species. We used a tropical bromeliad-dwelling frog as a model system to explore a cost-effective sampling design that optimizes the chances of detecting a population decline. Relatively few sampling visits were needed to estimate occupancy and detectability with good precision, and to detect a 30% change in occupancy with 80% power. Detectability was influenced by observer expertise, which therefore also had an effect on the sampling design - less experienced observers require more sampling visits to detect the species. Even when the sampling design provides precise parameter estimates, only moderate to large changes in occupancy will be detected with reliable power. Detecting a population change of 15% or less requires a large number of sites to be surveyed, which might be unachievable for range-restricted species occurring at relatively few sites. Unless there is high initial occupancy, rare and cryptic species will be particularly challenging when it comes to detecting small population changes. This may be a particular issue for long-term monitoring of amphibians which often display low detectability and wide natural fluctuations.

Density, abundance, survival, and ranging patterns of common bottlenose dolphins (Tursiops truncatus) in Mississippi Sound following the Deepwater Horizon oil spill

After the Deepwater Horizon (DWH) oil spill began in April 2010, studies were initiated on northern Gulf of Mexico common bottlenose dolphins (Tursiops truncatus) in Mississippi Sound (MSS) to determine density, abundance, and survival, during and after the oil spill, and to compare these results to previous research in this region. Seasonal boat-based photo-identification surveys (2010–2012) were conducted in a section of MSS to estimate dolphin density and survival, and satellite-linked telemetry (2013) was used to determine ranging patterns. Telemetry suggested two different ranging patterns in MSS: (1) inshore waters with seasonal movements into mid-MSS, and (2) around the barrier islands exclusively. Based upon these data, dolphin density was estimated in two strata (Inshore and Island) using a spatially-explicit robust-design capture-recapture model. Inshore and Island density varied between 0.77–1.61 dolphins km⁻² (x¯ = 1.42, 95% CI: 1.28–1.53) and 3.32–5.74 dolphins km⁻² (x¯ = 4.43, 95% CI: 2.70–5.63), respectively. The estimated annual survival rate for dolphins with distinctive fins was very low in the year following the spill, 0.73 (95% CI: 0.67–0.78), and consistent with the occurrence of a large scale cetacean unusual mortality event that was in part attributed to the DWH oil spill. Fluctuations in density were not as large or seasonally consistent as previously reported. Total abundance for MSS extrapolated from density results ranged from 4,610 in July 2011 to 3,046 in January 2012 (x¯ = 3,469, 95% CI: 3,113–3,725).

State-space mark-recapture estimates reveal a recent decline in abundance of North Atlantic right whales

North Atlantic right whales (Eubalaena glacialis Müller 1776) present an interesting problem for abundance and trend estimation in marine wildlife conservation. They are long lived, individually identifiable, highly mobile, and one of the rarest of cetaceans. Individuals are annually resighted at different rates, primarily due to varying stay durations among several principal habitats within a large geographic range. To date, characterizations of abundance have been produced that use simple accounting procedures with differing assumptions about mortality. To better characterize changing abundance of North Atlantic right whales between 1990 and 2015, we adapted a state–space formulation with Jolly‐Seber assumptions about population entry (birth and immigration) to individual resighting histories and fit it using empirical Bayes methodology. This hierarchical model included accommodation for the effect of the substantial individual capture heterogeneity. Estimates from this approach were only slightly higher than published accounting procedures, except for the most recent years (when recapture rates had declined substantially). North Atlantic right whales' abundance increased at about 2.8% per annum from median point estimates of 270 individuals in 1990 to 483 in 2010, and then declined to 2015, when the final estimate was 458 individuals (95% credible intervals 444–471). The probability that the population's trajectory post‐2010 was a decline was estimated at 99.99%. Of special concern was the finding that reduced survival rates of adult females relative to adult males have produced diverging abundance trends between sexes. Despite constraints in recent years, both biological (whales' distribution changing) and logistical (fewer resources available to collect individual photo‐identifications), it is still possible to detect this relatively recent, small change in the population's trajectory. This is thanks to the massive dataset of individual North Atlantic right whale identifications accrued over the past three decades. Photo‐identification data provide biological information that allows more informed inference on the status of this species.

Long-term genetic monitoring of a riverine dragonfly, Orthetrum coerulescens (Odonata: Libellulidae]: Direct anthropogenic impact versus climate change effects

Modern conservationists call for long term genetic monitoring datasets to evaluate and understand the impact of human activities on natural ecosystems and species on a global but also local scale. However, long-term monitoring datasets are still rare but in high demand to correctly identify, evaluate and respond to environmental changes. In the presented study, a population of the riverine dragonfly, Orthetrum coerulescens (Odonata: Libellulidae), was monitored over a time period from 1989 to 2013. Study site was an artificial irrigation ditch in one of the last European stone steppes and “nature heritage”, the Crau in Southern France. This artificial riverine habitat has an unusual high diversity of odonate species, prominent indicators for evaluating freshwater habitats. A clearing of the canal and destruction of the bank vegetation in 1996 was assumed to have great negative impact on the odonate larval and adult populations. Two mitochondrial markers (CO1 & ND1) and a panel of nuclear microsatellite loci were used to assess the genetic diversity. Over time they revealed a dramatic decline in diversity parameters between the years 2004 and 2007, however not between 1996 and 1997. From 2007 onwards the population shows a stabilizing trend but has not reached the amount of genetic variation found at the beginning of this survey. This decline cannot be referred to the clearing of the canal or any other direct anthropogenic impact. Instead, it is most likely that the populations’ decay was due to by extreme weather conditions during the specific years. A severe drought was recorded for the summer months of these years, leading to reduced water levels in the canal causing also other water parameters to change, and therefore impacting temperature sensitive riverine habitat specialists like the O. coerulescens in a significant way. The data provide important insights into population genetic dynamics and metrics not always congruent with traditional monitoring data (e.g. abundance); a fact that should be regarded with caution when management plans for developed landscapes are designed.

A Robust Design Capture-Recapture Analysis of Abundance, Survival and Temporary Emigration of Three Odontocete Species in the Gulf of Corinth, Greece

While the Mediterranean Sea has been designated as a Global Biodiversity Hotspot, assessments of cetacean population abundance are lacking for large portions of the region, particularly in the southern and eastern basins. The challenges and costs of obtaining the necessary data often result in absent or poor abundance information. We applied capture-recapture models to estimate abundance, survival and temporary emigration of odontocete populations within a 2,400 km² semi-enclosed Mediterranean bay, the Gulf of Corinth. Boat surveys were conducted in 2011–2015 to collect photo-identification data on striped dolphins Stenella coeruleoalba, short-beaked common dolphins Delphinus delphis (always found together with striped dolphins in mixed groups) and common bottlenose dolphins Tursiops truncatus, totaling 1,873 h of tracking. After grading images for quality and marking distinctiveness, 23,995 high-quality photos were included in a striped and common dolphin catalog, and 2,472 in a bottlenose dolphin catalog. The proportions of striped and common dolphins were calculated from the photographic sample and used to scale capture-recapture estimates. Best-fitting robust design capture-recapture models denoted no temporary emigration between years for striped and common dolphins, and random temporary emigration for bottlenose dolphins, suggesting different residency patterns in agreement with previous studies. Average estimated abundance over the five years was 1,331 (95% CI 1,122–1,578) striped dolphins, 22 (16–32) common dolphins, 55 (36–84) “intermediate” animals (potential striped x common dolphin hybrids) and 38 (32–46) bottlenose dolphins. Apparent survival was constant for striped, common and intermediate dolphins (0.94, 95% CI 0.92–0.96) and year-dependent for bottlenose dolphins (an average of 0.85, 95% CI 0.76–0.95). Our work underlines the importance of long-term monitoring to contribute reliable baseline information that can help assess the conservation status of wildlife populations.

The Gulf of Ambracia's Common Bottlenose Dolphins, Tursiops truncatus: A Highly Dense and yet Threatened Population

The common bottlenose dolphin (Tursiops truncatus) is the only cetacean present in the semiclosed waters of the Gulf of Ambracia, Western Greece. This increasingly degraded coastal ecosystem hosts one of the highest observed densities in the Mediterranean Sea for this species. Photo-identification data and tissue samples collected through skin-swabbing and remote biopsy sampling techniques during boat-based surveys conducted between 2006 and 2015 in the Gulf, were used to examine bottlenose dolphin abundance, population trends, site fidelity, genetic differentiation and toxicological status. Bottlenose dolphins showed high levels of year-round site fidelity throughout the 10-year study period. Dolphin population estimates mostly fell between 130 and 170 with CVs averaging about 10%; a trend in population size over the 10 years was a decline of 1.6% per year (but this was not significant). Genetic differentiation between the bottlenose dolphins of the Gulf and their conspecifics from neighbouring populations was detected, and low genetic diversity was found among individuals sampled. In addition, pesticides where identified as factors posing a real toxicological problem for local bottlenose dolphins. Therefore, in the Gulf of Ambracia, high dolphin density does not seem to be indicative of favourable conservation status or pristine habitat.