Environmental DNA (eDNA) methods are providing tools for detecting invasive species in aquatic environments. Targeted qPCR assays applied to eDNA samples promise to overcome limitations of traditional methods, especially for early detection. The European green crab (Carcinus maenas) is considered one of the most successful invasive species globally due to the large range it has invaded and negative impacts on native species, marine habitats, and shellfish industries. We developed, laboratory‐validated, and field‐tested a specific qPCR assay for the detection of green crab from eDNA samples. We also show that the assay can detect green crab in bulk DNA extracted from plankton samples. Assay design, optimization, sensitivity, and specificity testing generally followed the validation pathway recommended by the World Organization for Animal Health for assays used to manage global aquatic animal health and infectious disease. Assay specificity was verified in silico and in vitro by laboratory testing 26 nontarget species, none of which showed potential for amplification. Assay sensitivity was appropriately high, with the limit of detection approaching two gene copies/μl. The assay was field‐tested on eDNA samples collected from filtered seawater at five sites on the Pacific coast of Canada known to harbor green crab based on historical monitoring data; green crab DNA was amplified from all sites. We also present early pilot field testing of the assay done on bulk DNA extracted from plankton samples from four sites from Australia, two sites with and two sites without reported records of green crab presence. Green crab was detected at both sites with known green crab records. Significant inhibition was recorded for some plankton samples but not for eDNA samples. This is the first qPCR assay for detection of European green crab, providing researchers and managers with a valuable new tool to aid early detection and ongoing monitoring.
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.
Understanding the spatial distribution of human impacts on marine environments is necessary for maintaining healthy ecosystems and supporting ‘blue economies’. Realistic assessments of impact must consider the cumulative impacts of multiple, coincident threats and the differing vulnerabilities of ecosystems to these threats. Expert knowledge is often used to assess impact in marine ecosystems because empirical data are lacking; however, this introduces uncertainty into the results. As part of a spatial cumulative impact assessment for Spencer Gulf, South Australia, we asked experts to estimate score ranges (best-case, most-likely and worst-case), which accounted for their uncertainty about the effect of 32 threats on eight ecosystems. Expert scores were combined with data on the spatial pattern and intensity of threats to generate cumulative impact maps based on each of the three scoring scenarios, as well as simulations and maps of uncertainty. We compared our method, which explicitly accounts for the experts’ knowledge-based uncertainty, with other approaches and found that it provides smaller uncertainty bounds, leading to more constrained assessment results. Collecting these additional data on experts’ knowledge-based uncertainty provides transparency and simplifies interpretation of the outputs from spatial cumulative impact assessments, facilitating their application for sustainable resource management and conservation.
Caulerpa taxifolia is a pantropical green benthic marine macroalga, and one of the best known marine invasive species in temperate coastal habitats. In Australia, this species has been introduced to seven estuaries along New South Wales and one in South Australia. How this alga will perform under future climate change scenarios is however not well defined. This study experimentally assessed the effects of ocean acidification and global warming on the growth, photosynthetic performance and the bacterial community on two populations of C. taxifolia, one native and one invasive. A range of complex significant interactive effects between pH, temperature, and initial plant size on the growth of C. taxifolia were observed, but no effect of population origin and photosystem II (PSII) fluorescence quantum yield parameters were detected. No significant effects of the treatment combinations were observed on bacterial community richness or diversity. Only one bacterial species out of 1087 present on the algae showed significant changes between pH treatments at high temperature (24°C). This bacterium belonged to the genus Planctomyces and its relative abundance was more than 10 times higher in samples with low pH compared to the control. Higher plant growth was observed under all higher pCO2 and lower pH conditions suggesting that C. taxifolia will benefit from climate change, posing a potential higher risk in invaded locations.
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