Stress Resistance and Adaptation of the Aquatic Invasive Species Tubastraea Coccinea (Lesson, 1829) to Climate Change and Ocean Acidification

A great number of studies published on long-term ocean warming and increased acidification have forecasted changes in regional biodiversity preempted by aquatic invasive species (AIS). The present paper is focused on invasive Tubastraea coccinea (TC), an azooxanthellate AIS coral thriving in regions of the Gulf of Mexico, which has shown an ability to invade altered habitats, including endemic Indo-Pacific T. coccinea (TCP) populations. To determine if invasive TC are more stress resistant than endemic Indo-Pacific T. coccinea (TCP), authors measured tissue loss and heat shock protein 70 (HSP70) expression, using a full factorial design, post exposure to changes in pH (7.5 and 8.1) and heat stress (31 °C and 34 °C). Overall, the mean time required for TCP to reach 50% tissue loss (LD50) was less than observed for TC by a factor of 0.45 (p < 0.0003). Increasing temperature was found to be a significant main effect (p = 0.004), decreasing the LD50 by a factor of 0.58. Increasing acidity to pH 7.5 from 8.1 did not change the sensitivity of TC to temperature; however, TCP displayed increased sensitivity at 31 °C. Increases in the relative density of HSP70 (TC) were seen at all treatment levels. Hence, TC appears more robust compared to TCP and may emerge as a new dominant coral displacing endemic populations as a consequence of climate change.

Watercraft Decontamination Practices to Reduce the Viability of Aquatic Invasive Species Implicated in Overland Transport.

Recreational boating activities enable aquatic invasive species (AIS) dispersal among disconnected lakes, as invertebrates and plants caught on or contained within watercraft and equipment used in invaded waterbodies can survive overland transport. Resource management agencies worldwide recommend decontaminating watercraft and equipment using high water pressure, rinsing with hot water, or air-drying for up to seven days to inhibit this mode of secondary spread. There is a lack of studies on the efficacy of these methods under realistic conditions and considering feasibility for recreational boaters. Hence, we conducted experiments addressing this knowledge gap using AIS present in Ontario, namely zebra mussels (Dreissena polymorpha), banded mystery snails (Viviparus georgianus), spiny waterfleas (Bythotrephes cederstroemi), Eurasian watermilfoil (Myriophyllum spicatum), Carolina fanwort (Cabomba caroliniana), and European frogbit (Hydrocharis morsus-ranae). Washing at high pressures of 900-1200 psi removed the most biological material (90%) from surfaces. Brief (<10s) exposure to water at ≥60°C caused nearly 100% mortality among all species tested, except snails. Acclimation to temperatures from 15°C to 30°C before hot water exposure had little effect on the minimum temperature required for no survival. Air-drying durations producing complete mortality were ≥60h for zebra mussels and spiny waterfleas, and ≥6 days among plants, whereas survival remained high among snails after a week of air-drying. Hot water exposure followed by air-drying was more effective than either method separately against all species tested, reducing either the minimum water temperature or air-drying duration necessary. These findings can inform best management strategies against AIS spread.

Testing a Generalizable Machine Learning Workflow for Aquatic Invasive Species on Rainbow Trout (Oncorhynchus mykiss) in Northwest Montana

Biological invasions are accelerating worldwide, causing major ecological and economic impacts in aquatic ecosystems. The urgent decision-making needs of invasive species managers can be better met by the integration of biodiversity big data with large-domain models and data-driven products. Remotely sensed data products can be combined with existing invasive species occurrence data via machine learning models to provide the proactive spatial risk analysis necessary for implementing coordinated and agile management paradigms across large scales. We present a workflow that generates rapid spatial risk assessments on aquatic invasive species using occurrence data, spatially explicit environmental data, and an ensemble approach to species distribution modeling using five machine learning algorithms. For proof of concept and validation, we tested this workflow using extensive spatial and temporal hybridization and occurrence data from a well-studied, ongoing, and climate-driven species invasion in the upper Flathead River system in northwestern Montana, USA. Rainbow Trout (RBT; Oncorhynchus mykiss), an introduced species in the Flathead River basin, compete and readily hybridize with native Westslope Cutthroat Trout (WCT; O. clarkii lewisii), and the spread of RBT individuals and their alleles has been tracked for decades. We used remotely sensed and other geospatial data as key environmental predictors for projecting resultant habitat suitability to geographic space. The ensemble modeling technique yielded high accuracy predictions relative to 30-fold cross-validated datasets (87% 30-fold cross-validated accuracy score). Both top predictors and model performance relative to these predictors matched current understanding of the drivers of RBT invasion and habitat suitability, indicating that temperature is a major factor influencing the spread of invasive RBT and hybridization with native WCT. The congruence between more time-consuming modeling approaches and our rapid machine-learning approach suggest that this workflow could be applied more broadly to provide data-driven management information for early detection of potential invaders.

Optimizing the location of watercraft inspection stations to slow the spread of aquatic invasive species

The accidental spread of aquatic invasive species (AIS) by recreational boaters is a major concern of state and county environmental planners in the USA. While programs for watercraft inspection to educate boaters and slow AIS spread are common practice, large numbers of boats and waterbodies, together with limited budgets, make program design difficult. To facilitate program design, we developed an integer programming model for allocation of scarce inspection resources among lakes. Our model uses species-specific infestation status of lakes and estimates of boat movement between lakes. The objective is to select lakes for inspection stations to maximize the number of risky boats inspected, where risky boats are ones that move from infested to uninfested lakes. We apply our model in Stearns County in central Minnesota, USA, to prioritize lakes for inspection stations and evaluate alternative management objectives. With an objective of protecting uninfested lakes within and outside Stearns County, the optimal policy is to locate stations at infested lakes having the most boats departing for uninfested lakes inside and outside the county. With an objective of protecting only Stearns County lakes, the optimal policy is to locate stations at both infested and uninfested lakes having the riskiest boats arriving from within and outside the county and departing to in-county lakes. The tradeoff between these objectives is significant.

Advanced molecular-based surveillance of quagga and zebra mussels: A review of environmental DNA/RNA (eDNA/eRNA) studies and considerations for future directions

Sensitive methods, capable of rapidly and accurately detecting aquatic invasive species, are in demand. Molecular-based approaches, such as environmental DNA (eDNA) surveys, satisfy these requirements and have grown in popularity. As such, eDNA surveys could aid the effort to combat the colonisation and spread of two notoriously invasive freshwater mussel species, the quagga mussel (Dreissena rostriformis bugensis) and zebra mussel (D. polymorpha), through improved surveillance ability. Here, we provide a review of dreissenid eDNA literature (both grey and published), summarising efforts involved in the development of various assays for use in multiple different technologies (e.g. quantitative PCR, high-throughput sequencing and loop-mediated isothermal amplification) and sampling scenarios. We discuss important discoveries made along the way, including novel revelations involving environmental RNA (eRNA), as well as the advantages and limitations of available methods and instrumentation. In closing, we highlight critical remaining gaps, where further investigation could lead to advancements in dreissenid monitoring capacity.

Terrestrial protected areas maintain freshwater ecosystem resilience to costly aquatic invasive species in the Panama Canal

River damming is expected to proliferate across Tropical American Rivers in the forthcoming decades with expected declines in ecosystem health to costly invasive species. Historical data and modern aquatic plant surveys of one of the largest and oldest tropical dam projects (the > 100 years old Panama Canal) reveal that modern plant communities in areas adjacent to terrestrial Natural Protected Areas (tNPAs) retain a pre-damming community structure that is apparently more resistant to invasive species. Establishing tNPAs adjacent to impounded rivers could be a cost-effective nature-based solution for tropical reservoir management.