Quantum computing: a new paradigm for ecology.

A global technology arms race is underway to build evermore powerful and precise quantum computers. Quantum computers have the potential to tackle certain quantitative problems quicker than classical computers. The current focus of quantum computing is on pushing the boundaries of fundamental quantum information and commercial applications in industrial sectors, financial services, and other profit-led sectors, particularly where improvements in optimisation and sampling can improve increased economic return. We believe that ecologists could exploit the computational power of quantum computers because the statistical approaches commonly used in ecology already have proven pathways on quantum computers. Moreover, quantum computing could ultimately leapfrog our understanding of complex ecological systems, if the hardware, opportunity, and creativity of quantitative ecologists all align.

Measuring habitat quality for waterbirds: A review.

Quantifying habitat quality is dependent on measuring a site's relative contribution to population growth rate. This is challenging for studies of waterbirds, whose high mobility can decouple demographic rates from local habitat conditions and make sustained monitoring of individuals near-impossible. To overcome these challenges, biologists have used many direct and indirect proxies of waterbird habitat quality. However, consensus on what methods are most appropriate for a given scenario is lacking. We undertook a structured literature review of the methods used to quantify waterbird habitat quality, and provide a synthesis of the context-dependent strengths and limitations of those methods. Our search of the Web of Science and Scopus databases returned a sample of 666 studies, upon which our review was based. The reviewed studies assessed habitat quality by either measuring habitat attributes (e.g., food abundance, water quality, vegetation structure), or measuring attributes of the waterbirds themselves (e.g., demographic parameters, body condition, behavior, distribution). Measuring habitat attributes, although they are only indirectly related to demographic rates, has the advantage of being unaffected by waterbird behavioral stochasticity. Conversely, waterbird-derived measures (e.g., body condition, peck rates) may be more directly related to demographic rates than habitat variables, but may be subject to greater stochastic variation (e.g., behavioral change due to presence of conspecifics). Therefore, caution is needed to ensure that the measured variable does influence waterbird demographic rates. This assumption was usually based on ecological theory rather than empirical evidence. Our review highlighted that there is no single best, universally applicable method to quantify waterbird habitat quality. Individual project specifics (e.g., time frame, spatial scale, funding) will influence the choice of variables measured. Where possible, practitioners should measure variables most directly related to demographic rates. Generally, measuring multiple variables yields a better chance of accurately capturing the relationship between habitat characteristics and demographic rates.

Environment and shipping drive environmental DNA beta-diversity among commercial ports.

The spread of nonindigenous species by shipping is a large and growing global problem that harms coastal ecosystems and economies and may blur coastal biogeographical patterns. This study coupled eukaryotic environmental DNA (eDNA) metabarcoding with dissimilarity regression to test the hypothesis that ship-borne species spread homogenizes port communities. We first collected and metabarcoded water samples from ports in Europe, Asia, Australia and the Americas. We then calculated community dissimilarities between port pairs and tested for effects of environmental dissimilarity, biogeographical region and four alternative measures of ship-borne species transport risk. We predicted that higher shipping between ports would decrease community dissimilarity, that the effect of shipping would be small compared to that of environment dissimilarity and shared biogeography, and that more complex shipping risk metrics (which account for ballast water and stepping-stone spread) would perform better. Consistent with our hypotheses, community dissimilarities increased significantly with environmental dissimilarity and, to a lesser extent, decreased with ship-borne species transport risks, particularly if the ports had similar environments and stepping-stone risks were considered. Unexpectedly, we found no clear effect of shared biogeography, and that risk metrics incorporating estimates of ballast discharge did not offer more explanatory power than simpler traffic-based risks. Overall, we found that shipping homogenizes eukaryotic communities between ports in predictable ways, which could inform improvements in invasive species policy and management. We demonstrated the usefulness of eDNA metabarcoding and dissimilarity regression for disentangling the drivers of large-scale biodiversity patterns. We conclude by outlining logistical considerations and recommendations for future studies using this approach.

Leveraging a natural murine meiotic drive to suppress invasive populations.

Invasive rodents are a major cause of environmental damage and biodiversity loss, particularly on islands. Unlike insects, genetic biocontrol strategies including population-suppressing gene drives with biased inheritance have not been developed in mice. Here, we demonstrate a gene drive strategy (tCRISPR) that leverages super-Mendelian transmission of the t haplotype to spread inactivating mutations in a haplosufficient female fertility gene (Prl). Using spatially explicit individual-based in silico modeling, we show that tCRISPR can eradicate island populations under a range of realistic field-based parameter values. We also engineer transgenic tCRISPR mice that, crucially, exhibit biased transmission of the modified t haplotype and Prl mutations at levels our modeling predicts would be sufficient for eradication. This is an example of a feasible gene drive system for invasive alien rodent population control.

Novel passive detection approach reveals low breeding season survival and apparent lactation cost in a critically endangered cave bat.

Capture-mark-recapture/resight (CMR) methods are used for survival-rate studies, yet are often limited by small sample sizes. Advances in passive integrated transponder (PIT) technology have enabled passive detection or 'resight' of marked individuals using large antennas with greater read-ranges than previously possible. We used passively-detected resight data and CMR models to study survival rates of the southern bent-winged bat Miniopterus orianae bassanii, a critically endangered, cave-dwelling bat. Over three years, we used PIT-tagging to monitor 2966 individuals at the species' largest breeding aggregation, using daily detection data (> 1.6 million detections) to estimate seasonal survival probabilities, structured by age, sex and reproductive status, and parameterise population projection matrices. This has hitherto been impossible using traditional CMR methods due to disturbance risk and low recapture rates. Bats exhibited lowest apparent seasonal survival over summer and autumn, particularly for reproductive females in summer (when lactating) and juveniles in autumn (after weaning), and high survival in winter. Lowest survival rates coincided with severe drought in summer-autumn 2016, suggesting that dry conditions affect population viability. Under all likely demographic assumptions, population projection matrices suggested the population is in deterministic decline, requiring urgent action to reduce extinction risk. Passively-collected resight data can now be used in combination with CMR models to provide extensive, robust information for targeted wildlife population management.

Gene drives for vertebrate pest control: Realistic spatial modelling of eradication probabilities and times for island mouse populations.

Invasive alien species continue to threaten global biodiversity. CRISPR-based gene drives, which can theoretically spread through populations despite imparting a fitness cost, could be used to suppress or eradicate pest populations. We develop an individual-based, spatially explicit, stochastic model to simulate the ability of CRISPR-based homing and X chromosome shredding drives to eradicate populations of invasive house mice (Mus muculus) from islands. Using the model, we explore the interactive effect of the efficiency of the drive constructs and the spatial ecology of the target population on the outcome of a gene-drive release. We also consider the impact of polyandrous mating and sperm competition, which could compromise the efficacy of some gene-drive strategies. Our results show that both drive strategies could be used to eradicate large populations of mice. Whereas parameters related to drive efficiency and demography strongly influence drive performance, we find that sperm competition following polyandrous mating is unlikely to impact the outcome of an eradication effort substantially. Assumptions regarding the spatial ecology of mice influenced the probability of and time required for eradication, with short-range dispersal capacities and limited mate-search areas producing 'chase' dynamics across the island characterized by cycles of local extinction and recolonization by mice. We also show that highly efficient drives are not always optimal, when dispersal and mate-search capabilities are low. Rapid local population suppression around the introduction sites can cause loss of the gene drive before it can spread to the entire island. We conclude that, although the design of efficient gene drives is undoubtedly critical, accurate data on the spatial ecology of target species are critical for predicting the result of a gene-drive release.

Accelerometer informed time-energy budgets reveal the importance of temperature to the activity of a wild, arid zone canid.

BACKGROUND: Globally, arid regions are expanding and becoming hotter and drier with climate change. For medium and large bodied endotherms in the arid zone, the necessity to dissipate heat drives a range of adaptations, from behaviour to anatomy and physiology. Understanding how apex predators negotiate these landscapes and how they balance their energy is important as it may have broad impacts on ecosystem function. METHODS: We used tri-axial accelerometry (ACC) and GPS data collected from free-ranging dingoes in central Australia to investigate their activity-specific energetics, and activity patterns through time and space. We classified dingo activity into stationary, walking, and running behaviours, and estimated daily energy expenditure via activity-specific time-energy budgets developed using energy expenditure data derived from the literature. We tested whether dingoes behaviourally thermoregulate by modelling ODBA as a function of ambient temperature during the day and night. We used traditional distance measurements (GPS) as well as fine-scale activity (ODBA) data to assess their daily movement patterns. RESULTS: We retrieved ACC and GPS data from seven dingoes. Their mass-specific daily energy expenditure was significantly lower in summer (288 kJ kg- 1 day- 1) than winter (495 kJ kg- 1 day- 1; p = 0.03). Overall, dingoes were much less active during summer where 91% of their day was spent stationary in contrast to just 46% during winter. There was a sharp decrease in ODBA with increasing ambient temperature during the day (R2 = 0.59), whereas ODBA increased with increasing Ta at night (R2 = 0.39). Distance and ODBA were positively correlated (R = 0.65) and produced similar crepuscular patterns of activity. CONCLUSION: Our results indicate that ambient temperature may drive the behaviour of dingoes. Seasonal differences of daily energy expenditure in free-ranging eutherian mammals have been found in several species, though this was the first time it has been observed in a wild canid. We conclude that the negative relationship between dingo activity (ODBA) and ambient temperature during the day implies that high heat gain from solar radiation may be a factor limiting diurnal dingo activity in an arid environment.

Serological evidence of exposure to a coronavirus antigenically related to severe acute respiratory syndrome virus (SARS-CoV-1) in the Grey-headed flying fox (Pteropus poliocephalus).

Many infectious pathogens can be transmitted by highly mobile species, like bats that can act as reservoir hosts for viruses such as henipaviruses, lyssaviruses and coronaviruses. In this study, we investigated the seroepidemiology of protein antigens to Severe acute respiratory syndrome virus (SARS-CoV-1) and Middle eastern respiratory syndrome virus (MERS-CoV) in Grey-headed flying foxes (Pteropus poliocephalus) in Adelaide, Australia sampled between September 2015 and February 2018. A total of 301 serum samples were collected and evaluated using a multiplex Luminex binding assay, and median fluorescence intensity thresholds were determined using finite-mixture modelling. We found evidence of antibodies reactive to SARS-CoV-1 or a related antigen with 42.5% (CI: 34.3%-51.2%) seroprevalence but insufficient evidence of reactivity to MERS-CoV antigen. This study provides evidence that the Grey-headed flying foxes sampled in Adelaide have been exposed to a SARS-like coronavirus.

Seroprevalence of three paramyxoviruses; Hendra virus, Tioman virus, Cedar virus and a rhabdovirus, Australian bat lyssavirus, in a range expanding fruit bat, the Grey-headed flying fox (Pteropus poliocephalus).

Habitat-mediated global change is driving shifts in species' distributions which can alter the spatial risks associated with emerging zoonotic pathogens. Many emerging infectious pathogens are transmitted by highly mobile species, including bats, which can act as spill-over hosts for pathogenic viruses. Over three years, we investigated the seroepidemiology of paramyxoviruses and Australian bat lyssavirus in a range-expanding fruit bat, the Grey-headed flying fox (Pteropus poliocephalus), in a new camp in Adelaide, South Australia. Over six, biannual, sampling sessions, we quantified median florescent intensity (MFI) antibody levels for four viruses for a total of 297 individual bats using a multiplex Luminex binding assay. Where appropriate, florescence thresholds were determined using finite mixture modelling to classify bats' serological status. Overall, apparent seroprevalence of antibodies directed at Hendra, Cedar and Tioman virus antigens was 43.2%, 26.6% and 95.7%, respectively. We used hurdle models to explore correlates of seropositivity and antibody levels when seropositive. Increased body condition was significantly associated with Hendra seropositivity (Odds ratio = 3.67; p = 0.002) and Hendra virus levels were significantly higher in pregnant females (p = 0.002). While most bats were seropositive for Tioman virus, antibody levels for this virus were significantly higher in adults (p < 0.001). Unexpectedly, all sera were negative for Australian bat lyssavirus. Temporal variation in antibody levels suggests that antibodies to Hendra virus and Tioman virus may wax and wane on a seasonal basis. These findings suggest a common exposure to Hendra virus and other paramyxoviruses in this flying fox camp in South Australia.

Locally Fixed Alleles: A method to localize gene drive to island populations.

Invasive species pose a major threat to biodiversity on islands. While successes have been achieved using traditional removal methods, such as toxicants aimed at rodents, these approaches have limitations and various off-target effects on island ecosystems. Gene drive technologies designed to eliminate a population provide an alternative approach, but the potential for drive-bearing individuals to escape from the target release area and impact populations elsewhere is a major concern. Here we propose the "Locally Fixed Alleles" approach as a novel means for localizing elimination by a drive to an island population that exhibits significant genetic isolation from neighboring populations. Our approach is based on the assumption that in small island populations of rodents, genetic drift will lead to alleles at multiple genomic loci becoming fixed. In contrast, multiple alleles are likely to be maintained in larger populations on mainlands. Utilizing the high degree of genetic specificity achievable using homing drives, for example based on the CRISPR/Cas9 system, our approach aims at employing one or more locally fixed alleles as the target for a gene drive on a particular island. Using mathematical modeling, we explore the feasibility of this approach and the degree of localization that can be achieved. We show that across a wide range of parameter values, escape of the drive to a neighboring population in which the target allele is not fixed will at most lead to modest transient suppression of the non-target population. While the main focus of this paper is on elimination of a rodent pest from an island, we also discuss the utility of the locally fixed allele approach for the goals of population suppression or population replacement. Our analysis also provides a threshold condition for the ability of a gene drive to invade a partially resistant population.

Rodent gene drives for conservation: opportunities and data needs.

Invasive rodents impact biodiversity, human health and food security worldwide. The biodiversity impacts are particularly significant on islands, which are the primary sites of vertebrate extinctions and where we are reaching the limits of current control technologies. Gene drives may represent an effective approach to this challenge, but knowledge gaps remain in a number of areas. This paper is focused on what is currently known about natural and developing synthetic gene drive systems in mice, some key areas where key knowledge gaps exist, findings in a variety of disciplines relevant to those gaps and a brief consideration of how engagement at the regulatory, stakeholder and community levels can accompany and contribute to this effort. Our primary species focus is the house mouse, Mus musculus, as a genetic model system that is also an important invasive pest. Our primary application focus is the development of gene drive systems intended to reduce reproduction and potentially eliminate invasive rodents from islands. Gene drive technologies in rodents have the potential to produce significant benefits for biodiversity conservation, human health and food security. A broad-based, multidisciplinary approach is necessary to assess this potential in a transparent, effective and responsible manner.

Author Correction: Effects of sampling effort on biodiversity patterns estimated from environmental DNA metabarcoding surveys.

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has been fixed in the paper.

High detectability with low impact: Optimizing large PIT tracking systems for cave-dwelling bats.

Passive integrated transponder (PIT) tag technology permits the "resighting" of animals tagged for ecological research without the need for physical re-trapping. Whilst this is effective if animals pass within centimeters of tag readers, short-distance detection capabilities have prevented the use of this technology with many species. To address this problem, we optimized a large (15 m long) flexible antenna system to provide a c. 8 m2 vertical detection plane for detecting animals in flight. We installed antennas at two roosting caves, including the primary maternity cave, of the critically endangered southern bent-winged bat (Miniopterus orianae bassanii) in south-eastern Australia. Testing of these systems indicated PIT-tags could be detected up to 105 cm either side of the antenna plane. Over the course of a three-year study, we subcutaneously PIT-tagged 2,966 bats and logged over 1.4 million unique detections, with 97% of tagged bats detected at least once. The probability of encountering a tagged bat decreased with increasing environmental "noise" (unwanted signal) perceived by the system. During the study, we mitigated initial high noise levels by earthing both systems, which contributed to an increase in daily detection probability (based on the proportion of individuals known to be alive that were detected each day) from <0.2 (noise level ≥30%) to 0.7-0.8 (noise level 5%-15%). Conditional on a low (5%) noise level, model-based estimates of daily encounter probability were highest (>0.8) during peak breeding season when both female and male southern bent-winged bats congregate at the maternity cave. In this paper, we detail the methods employed and make methodological recommendations for future wildlife research using large antennas, including earthing systems as standard protocol and quantifying noise metrics as a covariate influencing the probability of detection in subsequent analyses. Our results demonstrate that large PIT antennas can be used successfully to detect small volant species, extending the scope of PIT technology and enabling a much broader range of wildlife species to be studied using this approach.

The potential of genomics for restoring ecosystems and biodiversity.

Billions of hectares of natural ecosystems have been degraded through human actions. The global community has agreed on targets to halt and reverse these declines, and the restoration sector faces the important but arduous task of implementing programmes to meet these objectives. Existing and emerging genomics tools offer the potential to improve the odds of achieving these targets. These tools include population genomics that can improve seed sourcing, meta-omics that can improve assessment and monitoring of restoration outcomes, and genome editing that can generate novel genotypes for restoring challenging environments. We identify barriers to adopting these tools in a restoration context and emphasize that regulatory and ethical frameworks are required to guide their use.

Incorporating intraspecific variation into dental microwear texture analysis.

Dental microwear texture analysis (DMTA) quantifies microscopic scar or wear patterns left on teeth by different foods or extraneous ingested items such as grit. It can be a powerful tool for deducing the diets of extinct mammals. Here we investigate how intraspecific variation in the dental microwear of macropodids (kangaroos and their close relatives) can be used to maximize the dietary signal inferable from an inherently limited fossil record. We demonstrate significant intraspecific variation for every factor considered here for both scale-sensitive fractal analysis and International Organization for Standardization surface texture analysis variables. Intraspecific factors were then incorporated into interspecific (dietary) analyses through the use of Linear Mixed Effects modelling, incorporating Akaike's Information Criterion to compare models, and testing models through independent cross-validation. This revealed that for each DMTA variable only a small number of intraspecific factors need to be included to improve differentiation between species. Including specimen as a random factor accounted for stochastic inter-individual variation, and facet, incorporated effects of sampling location. Intraspecific effects of ecoregion, microscope, tooth position and wear were often but not universally important. We conclude that models of microwear data that include intraspecific variation can improve the resolution of dietary reconstructions.

Bonamia in Ostrea angasi: Diagnostic performance, field prevalence and intensity.

Bonamia spp. parasites threaten flat oyster (Ostrea spp.) farming worldwide. Understanding test performance is important for designing surveillance and interpreting diagnostic results. Following a pilot survey which found low Bonamia sp. intensity in farmed Ostrea angasi, we tested further oysters (n = 100-150) from each of three farms for Bonamia sp. using heart smear, histology and qPCR. We used a Bayesian Latent Class Model to assess diagnostic sensitivity (DSe) and specificity (DSp) of these tests individually or in combination, and to assess prevalence. Histology was the best individual test (DSe 0.76, DSp 0.93) compared to quantitative polymerase chain reaction (qPCR) (DSe 0.69, DSp 0.93) and heart smear (DSe 0.61, DSp 0.60). Histology combined with qPCR and defining a positive from either test as an infected case maximized test performance (DSe 0.91, DSp 0.88). Prevalence was higher at two farms in a high-density oyster growing region than at a farm cultivating oysters at lower density. Parasite intensities were lower than in New Zealand and European studies, and this is probably contributed to differences in the performance of test when compared to other studies. Understanding diagnostic test performance in different populations can support the development of improved Bonamia surveillance programs.

A concise guide to developing and using quantitative models in conservation management.

Quantitative models are powerful tools for informing conservation management and decision-making. As applied modeling is increasingly used to address conservation problems, guidelines are required to clarify the scope of modeling applications and to facilitate the impact and acceptance of models by practitioners. We identify three key roles for quantitative models in conservation management: (a) to assess the extent of a conservation problem; (b) to provide insights into the dynamics of complex social and ecological systems; and, (c) to evaluate the efficacy of proposed conservation interventions. We describe 10 recommendations to facilitate the acceptance of quantitative models in conservation management, providing a basis for good practice to guide their development and evaluation in conservation applications. We structure these recommendations within four established phases of model construction, enabling their integration within existing workflows: (a) design (two recommendations); (b) specification (two); (c) evaluation (one); and (d) inference (five). Quantitative modeling can support effective conservation management provided that both managers and modelers understand and agree on the place for models in conservation. Our concise review and recommendations will assist conservation managers and modelers to collaborate in the development of quantitative models that are fit-for-purpose, and to trust and use these models appropriately while understanding key drivers of uncertainty.

High accuracy at low frequency: detailed behavioural classification from accelerometer data.

Accelerometers are a valuable tool for studying animal behaviour and physiology where direct observation is unfeasible. However, giving biological meaning to multivariate acceleration data is challenging. Here, we describe a method that reliably classifies a large number of behaviours using tri-axial accelerometer data collected at the low sampling frequency of 1 Hz, using the dingo (Canis dingo) as an example. We used out-of-sample validation to compare the predictive performance of four commonly used classification models (random forest, k-nearest neighbour, support vector machine, and naïve Bayes). We tested the importance of predictor variable selection and moving window size for the classification of each behaviour and overall model performance. Random forests produced the highest out-of-sample classification accuracy, with our best-performing model predicting 14 behaviours with a mean accuracy of 87%. We also investigated the relationship between overall dynamic body acceleration (ODBA) and the activity level of each behaviour, given the increasing use of ODBA in ecophysiology as a proxy for energy expenditure. ODBA values for our four 'high activity' behaviours were significantly greater than all other behaviours, with an overall positive trend between ODBA and intensity of movement. We show that a random forest model of relatively low complexity can mitigate some major challenges associated with establishing meaningful ecological conclusions from acceleration data. Our approach has broad applicability to free-ranging terrestrial quadrupeds of comparable size. Our use of a low sampling frequency shows potential for deploying accelerometers over extended time periods, enabling the capture of invaluable behavioural and physiological data across different ontogenies.

Pest demography critically determines the viability of synthetic gene drives for population control.

Synthetic gene drives offer a novel solution for the control of invasive alien species. CRISPR-based gene drives can positively bias their own inheritance, and comprise a DNA sequence that is replicated by homologous recombination. Since gene drives can be positioned to silence fertility or developmental genes, they could be used for population suppression. However, the production of resistant alleles following self-replication errors threatens the technology's viability for pest eradication in real-world applications. Further, a robust assessment of how pest demography impacts the expected progression of gene drives through populations is currently lacking. We used a deterministic, two-sex, birth-death model to investigate how demographic assumptions affect the efficiency of suppression drives for controlling invasive rodents on islands, for two different gene-drive strategies. We show that mass-action reproduction results in overly optimistic eradication outcomes when compared to the more realistic assumption of polygynous breeding. When polygyny was assumed, both gene-strategies failed due to the evolution of resistance unless a reproductive Allee effect (reduced reproductive rates at low population density) was also included; although model outcomes were highly sensitive to the strength of this effect. Increasing the size of the initial gene-drive introduction (up to 10% of carrying capacity) had little impact on population outcomes. Understanding the demography of a population targeted for eradication is critical before the viability of gene-drive suppression can be adequately assessed.