Quantitative Tools for Monitoring Strategy Evaluation and Assessment of Sea Turtle Populations

Green sea turtles, Chelonia mydas, have endangered and threatened populations globally, but several populations show signs of population recovery. In Hawaii, nesting female green turtles have increased 5.7% year⁻¹ since 1973, but wide fluctuations in census counts of nesting females make recovery diagnosis difficult. For effective management planning, it is critical to have the best information possible on vital rates, and to determine the best tools and practices for incorporating vital rate information, particularly variability, into population models to assess population size and status. Process and observation errors, compounded by late maturity, obscure the relationship between trends on the nesting beach and the entire population. Using sea turtle nesting beach surveys as a population index for assessment is problematic, yet often pragmatic because this is the only population index that is easily accessible. It is advantageous to use a modelling approach that estimates interannual variability in life history traits, accounts for uncertainty from individual-level variability, and allows for population dynamics to emerge from individual behaviors. To this end, I analyzed a long-term data set of marked green sea turtles to determine the degree of temporal variability in key life history traits. From this analysis, I built an agent-based model (ABM) to form the basis of a new assessment tool -- Monitoring Strategy Evaluation. In Chapter 2, I evaluated annual changes in demographic indicators (DIs) of 3,677 nesting green turtles from a 38-year tagging program in the Hawaiian Islands to determine if key life history traits are changing over time and in response to nester density. I used linear mixed models and multistate open robust design models to estimate several DIs and correlated them with nesting female counts. Mean nester carapace length and breeding probability were highly variable over time, suggesting shifts in age structure that could be due to recruitment. The top-ranked model predicted constant female survival over time. A significant positive relationship between the nesting population and breeding probability was evident, and breeding probability shows promise as an indicator of population recovery. This work contributes to a growing set of studies evaluating sea turtle demography for temporal variability and is the first for Hawaiian green turtles. In Chapter 3, I develop the Green Sea Turtle Agent-Based Model (GSTABM) to evaluate how recovery processes differ across disturbance types. The GSTABM incorporates individually variable age-at-maturity, clutch frequency and clutch size, annually variable breeding probability, environmental stochasticity and density dependence in hatchling production. The GSTABM simulates the process of population impact and recovery and the monitoring process, with observation error, on the nesting beach. The GSTABM captures the emergent patterns of interannual nesting variation, nester recruitment, and realistic population growth rates. Changes in survival rates of the nearshore age-stage classes directly affected adult and nester abundance, population growth rate and nester recruitment more than any of the other input parameters. In simulating 100 years of recovery, experimentally disturbed populations began to increase but did not fully return to pre-disturbance levels in adult and nester abundance, population growth or nester recruitment. In simulations with different levels of monitoring effort, adult abundance was poorly estimated, was influenced by population trajectory and disturbance type, and showed marginal improvements in accuracy with increased detection probability. Estimating recruitment showed improvements with increasing detection levels. In the GSTABM, variability in the nesting beach does not mirror variability in adult abundance. The GSTABM is an important tool to determine relationships with monitoring, population assessment, and the underlying biological processes driving changes in the population, and especially, changes on the nesting beach. In Chapter 4, I develop a new simulation-based tool: Monitoring Strategy Evaluation (MoSE) to determine which data source yields the most useful information for population assessments. The MoSE has three main components: the simulated "true" operating, observation, and estimation models. To explore this first use of MoSE, I apply different treatments of disturbance, sampling, and detection to the virtual "true" population, and then sample the nests or nesters, with observation error, to test if the observation "data" accurately diagnose population status indicators. Based on the observed data, I estimated adult abundance, nester recruitment, and population trend and compare them to the known values. I tested the accuracy of the estimated abundance when annually varying inputs of breeding probability, detection and clutch frequency were used instead of constants. I also explored the improvement of trend accuracy with increased study duration. Disturbance type and severity can have important and persistent effects on the accuracy of population assessments drawn from monitoring rookeries. Accuracy in abundance estimates may be most improved by avoiding clutch frequency bias in sampling and including annually varying inputs in the estimation model. Accuracy of nester recruitment may be most improved by increasing detection level and avoiding age-bias in sampling. The accuracy of estimating population trend is most influenced by the underlying population trajectory, disturbance type and disturbance severity. At least 10 years of monitoring data are necessary to accurately estimate population trend, and longer if juvenile age classes were disturbed and trend estimates occur during the recovery phase. The MoSE is an important tool for sea turtle biologists and conservation managers and allows biologists to make informed decisions regarding the best monitoring strategies to employ for sea turtles. This modeling framework is designed to provide an evaluation of monitoring program effectiveness to assist in planning future programs for sea turtles. Altogether, my research suggests certain life history traits of green sea turtles have important temporal variation that should be accounted for in population models, understanding the relationships between nesting and the total population is essential, and basing population assessments from nesting beach data alone is likely to result in incorrect or biased estimates of status indicators. The quantitative tools employed here can be applied to other sea turtle populations and will improve monitoring, and result in better estimates of current population trends and enhance conservation for all species of sea turtles

Evaluating Temporal Consistency in Marine Biodiversity Hotspots

With the ongoing crisis of biodiversity loss and limited resources for conservation, the concept of biodiversity hotspots has been useful in determining conservation priority areas. However, there has been limited research into how temporal variability in biodiversity may influence conservation area prioritization. To address this information gap, we present an approach to evaluate the temporal consistency of biodiversity hotspots in large marine ecosystems. Using a large scale, public monitoring dataset collected over an eight year period off the US Pacific Coast, we developed a methodological approach for avoiding biases associated with hotspot delineation. We aggregated benthic fish species data from research trawls and calculated mean hotspot thresholds for fish species richness and Shannon’s diversity indices over the eight year dataset. We used a spatial frequency distribution method to assign hotspot designations to the grid cells annually. We found no areas containing consistently high biodiversity through the entire study period based on the mean thresholds, and no grid cell was designated as a hotspot for greater than 50% of the time-series. To test if our approach was sensitive to sampling effort and the geographic extent of the survey, we followed a similar routine for the northern region of the survey area. Our finding of low consistency in benthic fish biodiversity hotspots over time was upheld, regardless of biodiversity metric used, whether thresholds were calculated per year or across all years, or the spatial extent for which we calculated thresholds and identified hotspots. Our results suggest that static measures of benthic fish biodiversity off the US West Coast are insufficient for identification of hotspots and that long-term data are required to appropriately identify patterns of high temporal variability in biodiversity for these highly mobile taxa. Given that ecological communities are responding to a changing climate and other environmental perturbations, our work highlights the need for scientists and conservation managers to consider both spatial and temporal dynamics when designating biodiversity hotspots

Patterns and Variation in Benthic Biodiversity in a Large Marine Ecosystem

While there is a persistent inverse relationship between latitude and species diversity across many taxa and ecosystems, deviations from this norm offer an opportunity to understand the conditions that contribute to large-scale diversity patterns. Marine systems, in particular, provide such an opportunity, as marine diversity does not always follow a strict latitudinal gradient, perhaps because several hypothesized drivers of the latitudinal diversity gradient are uncorrelated in marine systems. We used a large scale public monitoring dataset collected over an eight year period to examine benthic marine faunal biodiversity patterns for the continental shelf (55–183 m depth) and slope habitats (184–1280 m depth) off the US West Coast (47°20′N—32°40′N). We specifically asked whether marine biodiversity followed a strict latitudinal gradient, and if these latitudinal patterns varied across depth, in different benthic substrates, and over ecological time scales. Further, we subdivided our study area into three smaller regions to test whether coast-wide patterns of biodiversity held at regional scales, where local oceanographic processes tend to influence community structure and function. Overall, we found complex patterns of biodiversity on both the coast-wide and regional scales that differed by taxonomic group. Importantly, marine biodiversity was not always highest at low latitudes. We found that latitude, depth, substrate, and year were all important descriptors of fish and invertebrate diversity. Invertebrate richness and taxonomic diversity were highest at high latitudes and in deeper waters. Fish richness also increased with latitude, but exhibited a hump-shaped relationship with depth, increasing with depth up to the continental shelf break, ~200 m depth, and then decreasing in deeper waters. We found relationships between fish taxonomic and functional diversity and latitude, depth, substrate, and time at the regional scale, but not at the coast-wide scale, suggesting that coast-wide patterns can obscure important correlates at smaller scales. Our study provides insight into complex diversity patterns of the deep water soft substrate benthic ecosystems off the US West Coast

Comparative Genomics of Gardnerella vaginalis Strains Reveals Substantial Differences in Metabolic and Virulence Potential

Gardnerella vaginalis is described as a common vaginal bacterial species whose presence correlates strongly with bacterial vaginosis (BV). Here we report the genome sequencing and comparative analyses of three strains of G. vaginalis. Strains 317 (ATCC 14019) and 594 (ATCC 14018) were isolated from the vaginal tracts of women with symptomatic BV, while Strain 409-05 was isolated from a healthy, asymptomatic individual with a Nugent score of 9.Substantial genomic rearrangement and heterogeneity were observed that appeared to have resulted from both mobile elements and substantial lateral gene transfer. These genomic differences translated to differences in metabolic potential. All strains are equipped with significant virulence potential, including genes encoding the previously described vaginolysin, pili for cytoadhesion, EPS biosynthetic genes for biofilm formation, and antimicrobial resistance systems, We also observed systems promoting multi-drug and lantibiotic extrusion. All G. vaginalis strains possess a large number of genes that may enhance their ability to compete with and exclude other vaginal colonists. These include up to six toxin-antitoxin systems and up to nine additional antitoxins lacking cognate toxins, several of which are clustered within each genome. All strains encode bacteriocidal toxins, including two lysozyme-like toxins produced uniquely by strain 409-05. Interestingly, the BV isolates encode numerous proteins not found in strain 409-05 that likely increase their pathogenic potential. These include enzymes enabling mucin degradation, a trait previously described to strongly correlate with BV, although commonly attributed to non-G. vaginalis species.Collectively, our results indicate that all three strains are able to thrive in vaginal environments, and therein the BV isolates are capable of occupying a niche that is unique from 409-05. Each strain has significant virulence potential, although genomic and metabolic differences, such as the ability to degrade mucin, indicate that the detection of G. vaginalis in the vaginal tract provides only partial information on the physiological potential of the organism

Mortality and pulmonary complications in patients undergoing surgery with perioperative SARS-CoV-2 infection: an international cohort study

Background: The impact of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) on postoperative recovery needs to be understood to inform clinical decision making during and after the COVID-19 pandemic. This study reports 30-day mortality and pulmonary complication rates in patients with perioperative SARS-CoV-2 infection. Methods: This international, multicentre, cohort study at 235 hospitals in 24 countries included all patients undergoing surgery who had SARS-CoV-2 infection confirmed within 7 days before or 30 days after surgery. The primary outcome measure was 30-day postoperative mortality and was assessed in all enrolled patients. The main secondary outcome measure was pulmonary complications, defined as pneumonia, acute respiratory distress syndrome, or unexpected postoperative ventilation. Findings: This analysis includes 1128 patients who had surgery between Jan 1 and March 31, 2020, of whom 835 (74·0%) had emergency surgery and 280 (24·8%) had elective surgery. SARS-CoV-2 infection was confirmed preoperatively in 294 (26·1%) patients. 30-day mortality was 23·8% (268 of 1128). Pulmonary complications occurred in 577 (51·2%) of 1128 patients; 30-day mortality in these patients was 38·0% (219 of 577), accounting for 81·7% (219 of 268) of all deaths. In adjusted analyses, 30-day mortality was associated with male sex (odds ratio 1·75 [95% CI 1·28–2·40], p\textless0·0001), age 70 years or older versus younger than 70 years (2·30 [1·65–3·22], p\textless0·0001), American Society of Anesthesiologists grades 3–5 versus grades 1–2 (2·35 [1·57–3·53], p\textless0·0001), malignant versus benign or obstetric diagnosis (1·55 [1·01–2·39], p=0·046), emergency versus elective surgery (1·67 [1·06–2·63], p=0·026), and major versus minor surgery (1·52 [1·01–2·31], p=0·047). Interpretation: Postoperative pulmonary complications occur in half of patients with perioperative SARS-CoV-2 infection and are associated with high mortality. Thresholds for surgery during the COVID-19 pandemic should be higher than during normal practice, particularly in men aged 70 years and older. Consideration should be given for postponing non-urgent procedures and promoting non-operative treatment to delay or avoid the need for surgery. Funding: National Institute for Health Research (NIHR), Association of Coloproctology of Great Britain and Ireland, Bowel and Cancer Research, Bowel Disease Research Foundation, Association of Upper Gastrointestinal Surgeons, British Association of Surgical Oncology, British Gynaecological Cancer Society, European Society of Coloproctology, NIHR Academy, Sarcoma UK, Vascular Society for Great Britain and Ireland, and Yorkshire Cancer Research

Validating the use of stereo‐video cameras to conduct remote measurements of sea turtles

Abstract Point 1: Stereo‐video camera systems (SVCSs) are a promising tool to remotely measure body size of wild animals without the need for animal handling. Here, we assessed the accuracy of SVCSs for measuring straight carapace length (SCL) of sea turtles. Point 2: To achieve this, we hand captured and measured 63 juvenile, subadult, and adult sea turtles across three species: greens, Chelonia mydas (n = 52); loggerheads, Caretta caretta (n = 8); and Kemp's ridley, Lepidochelys kempii (n = 3) in the waters off Eleuthera, The Bahamas and Crystal River, Florida, USA, between May and November 2019. Upon release, we filmed these individuals with the SVCS. We performed photogrammetric analysis to extract stereo SCL measurements (eSCL), which were then compared to the (manual) capture measurements (mSCL). Point 3: mSCL ranged from 25.9 to 89.2 cm, while eSCL ranged from 24.7 to 91.4 cm. Mean percent bias of eSCL ranged from −0.61% (±0.11 SE) to −4.46% (±0.31 SE) across all species and locations. We statistically analyzed potential drivers of measurement error, including distance of the turtle to the SVCS, turtle angle, image quality, turtle size, capture location, and species. Point 4: Using a linear mixed effects model, we found that the distance between the turtle and the SVCS was the primary factor influencing measurement error. Our research suggests that stereo‐video technology enables high‐quality measurements of sea turtle body size collected in situ without the need for hand‐capturing individuals. This study contributes to the growing knowledge base that SVCS are accurate for body size measurements independent of taxonomic clade

Size-Mediated Sea Turtle Behavioral Responses at Artificial Habitats in the Northern Gulf of Mexico

Our understanding of size-specific sea turtle behavior has lagged due to methodological limitations. However, stereo-video cameras (SVC) are an in-water approach that can link body-size and allow for relatively undisturbed behavioral observations. In this study, we conducted SVC dive surveys at local artificial reefs, piers, and jetties in the northern Gulf of Mexico (nGOM) from May 2019 to August 2021. Using SVCs, we measured sea turtle straight carapace length, documented behaviors, and quantified wariness by assessing minimum approach distance (MAD). In green sea turtles (Chelonia mydas), the observed MAD ranged from 0.72 to 5.99 m (mean 2.10 m ± 1.10 standard deviation (SD), n = 73). For loggerhead sea turtles (Caretta caretta), the MAD ranged between 0.93 and 3.80 m (mean 2.12 m ± 0.99 SD, n = 16). Kemp’s ridley sea turtles (Lepidochelys kempii) were similar to loggerheads, and MAD ranged from 0.78 to 3.63 m (mean 2.35 m ± 0.99 SD, n = 8). We then evaluated what biological factors could impact the MAD observed by species, but we excluded Kemp’s ridleys as the sample size was small. Using a linear mixed model and model selection based on AICc, the top ranked model for both green and loggerhead sea turtles included SCL as the most important factor influencing MAD. MAD did not vary with habitat type for either species. Our results showed that larger individuals, regardless of species, have a greater wariness response, becoming startled at greater distances than smaller individuals. The findings of our study support the use of SVC as an accessible, non-invasive tool to conduct ecologically relevant in-water surveys of sea turtles to link behavioral observations to body size

Evaluating Temporal Consistency in Marine Biodiversity Hotspots

<div><p>With the ongoing crisis of biodiversity loss and limited resources for conservation, the concept of biodiversity hotspots has been useful in determining conservation priority areas. However, there has been limited research into how temporal variability in biodiversity may influence conservation area prioritization. To address this information gap, we present an approach to evaluate the temporal consistency of biodiversity hotspots in large marine ecosystems. Using a large scale, public monitoring dataset collected over an eight year period off the US Pacific Coast, we developed a methodological approach for avoiding biases associated with hotspot delineation. We aggregated benthic fish species data from research trawls and calculated mean hotspot thresholds for fish species richness and Shannon’s diversity indices over the eight year dataset. We used a spatial frequency distribution method to assign hotspot designations to the grid cells annually. We found no areas containing consistently high biodiversity through the entire study period based on the mean thresholds, and no grid cell was designated as a hotspot for greater than 50% of the time-series. To test if our approach was sensitive to sampling effort and the geographic extent of the survey, we followed a similar routine for the northern region of the survey area. Our finding of low consistency in benthic fish biodiversity hotspots over time was upheld, regardless of biodiversity metric used, whether thresholds were calculated per year or across all years, or the spatial extent for which we calculated thresholds and identified hotspots. Our results suggest that static measures of benthic fish biodiversity off the US West Coast are insufficient for identification of hotspots and that long-term data are required to appropriately identify patterns of high temporal variability in biodiversity for these highly mobile taxa. Given that ecological communities are responding to a changing climate and other environmental perturbations, our work highlights the need for scientists and conservation managers to consider both spatial and temporal dynamics when designating biodiversity hotspots.</p></div

North Biogeographic region—location of 1600 km² grid cells with ≥ 3 scientific trawls/year and hotspots for A) benthic fish species richness, and B) benthic fish Shannon diversity, H′.

<p>Each grid cell contains an identification number and shading indicates the number of years (out of 8, 2003–2010) that the cell exceeded the universal threshold value to be classified as a hotspot (31.1 for species richness, 2.37 for Shannon diversity H′).</p

Number of grid cells (and percentage of total) designated as benthic fish biodiversity hotspots (temporal consistency ranging from 0 years hot to 8 years hot) for Coast-wide and the North biogeographic regions and for the minimum, mean, and maximum universal thresholds and annual threshold calculated for 2003–2010.

<p>Number of grid cells (and percentage of total) designated as benthic fish biodiversity hotspots (temporal consistency ranging from 0 years hot to 8 years hot) for Coast-wide and the North biogeographic regions and for the minimum, mean, and maximum universal thresholds and annual threshold calculated for 2003–2010.</p