A: Environmental DNA, or eDNA, sheds into the environment by an organism from various means such as mucus, feces, or reproductive activities. Using eDNA to detect and quantify aquatic nuisance species offers reliable information that, when used along with traditional aquatic surveys, improves rapid response and invasive species control programs.​​   

A: An eDNA monitoring strategy can be cost-effective for determining species occurrence or relative abundance when traditional methods of monitoring (e.g., field surveys) fail to effectively sample the environment. Existing field surveys suffer from changing and unpredictable environmental conditions, gear saturation, poor catchability of species, staff and equipment demands, and patchy sampling. Incorporating an eDNA monitoring strategy compliments existing field surveys because they can expand the geographic range of detection, provide an additional index of relative abundance or density, and can create an early-warning system, potentially giving a one or two year alert prior to detecting the species with traditional field survey gear.   

A: Identify objectives. The researcher must determine whether they are interested in targeting a species, enumerating a species, detecting multiple species, and using the results to further explore patterns of population genetics, such as relatedness or genetic diversity.   

For projects that target a species, its genomic sequence must be able to be referenced as a positive control. Aquatic Nuisance Species of Maryland with positive controls include: northern snakehead, blue catfish, flathead catfish, grass carp, silver and bighead carp, hydrilla, Eurasian watermilfoil, water chestnut, zebra mussel, New Zealand mudsnail, rusty crayfish, and golden algae.   

Once a target species is identified, a researcher must decide whether their objective is to detect a species or to index relative abundance or density. In some cases, multiple target species can be screened using metabarcoding. This can be useful for roughly estimating biodiversity metrics.   

A researcher must also decide on the DNA marker or gene of the species to target. Mitochondrial DNA (e.g., cytochrome B) are more numerous in water samples and degrade less quickly than nuclear markers. Nuclear markers (e.g., microsatellites) provide more detailed information for population genetics because they are inherited by both parents and recombine during cellular division.   

A: Anyone. Public engagement projects help improve staffing. Because plan development often includes robust field sampling and lab standards, identifying several sources of participants can be important. Departmental staff or citizen scientists can collect samples. Adequate education, standard operating procedures, proper QA/QC procedures, and training helps minimize contamination of samples. To maintain engagement of citizen scientists, the department should: 1) target a community with interest in the resource; and 2) combine eDNA collection with other, immediately obtainable measures (e.g., Secchi disk measures).​    

A:  Methods may vary among projects and depend on the objectives of the research.  For detection or enumeration of a target species in Maryland, the department has 20 assembled kits for sampling eDNA for testing up to 1,400 individual samples.  These samples are tested in partnership with the United States Geological Survey (National Fish Health Research Laboratory, Leetown, West Virginia).  For more information, please contact [email protected].   

Material List:  1) latex gloves; 2) 500 ml container; 3) label for container; 4) flocculent vial; 5) towel; 6) permanent marker; 7) cooler with ice.   

1.  Identify a convenient and suitable site and time for water collection (see Reduce Bias, below) - please record GPS latitude and longitude.   

2.  Wearing gloves, fill a 500 milliliter container to, but not above, the shoulder with the site's water. This will be approximately 450 milliliters. Sample surface water about 1 arm length from your body to avoid contamination.  Cap the water sample and label the outside with date, location, and contact name and email.  Store ON ICE until returning from a sampling trip.    

3.  Repeat Step 2 an additional three times, at the same or different locations or times, until four, 500 milliliter containers have water samples.  All samples will be pooled for eDNA analysis.   

4.  Wipe the outside of the sample bottle with a clean paper towel to remove any liquid from around the cap.  Then open the sample bottle away from your body and add the entire contents of a vial of flocculent.  Recap tightly and mix.    

5.  Label container with supplied label.  Include date and location.  Write date, location, and collector's name and contact information in the field guide supplied with the kit.     

6.  Freeze the samples until transport to the lab.  NOTE – eDNA can degrade within two days in warm water.   

7.  Contact Luke Iwanowicz ([email protected]) and William (Bane) Schill ([email protected]) to make arrangements of sample transportation.  Carbon [email protected].  Arrange to have samples driven to Luke and Bane, or store samples until a shipment can be driven to Luke and Bane.​
   

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A:  Allochthonous or unwanted DNA can cross-contaminate samples and a Standard Operating Procedure (SOP) minimizes cross-contamination. A blank control and duplicate samples are recommended.  When developing a SOP, the following things should be considered:   

1. More eDNA is shed by mobile or active fish, spawning fish, and in warmer water.  Predicting abundance using eDNA from crustaceans is more difficult than for fish and easiest for sessile organisms, such as coral and sea stars.  Taxonomic aspects must be considered to ensure samples are taken at times and in areas where the species is most likely to occur. 
2. Areas where carcasses of the target species can be discarded, or at locations where legacy eDNA may remain in sediments, must be avoided.
3. Abundance estimated using eDNA is more effective in mesocosms or laboratory experiments than in field experiments because of numerous covariates that affect sampling of eDNA. 
1. Use of eDNA can be inhibited or influenced by water temperature and pH.
2. Use of eDNA can be difficult when diluted with rainfall, stream flow, and tidal flushing.
3. Lotic systems may require a special flow correction to estimate abundance from eDNA, unless samples are taken at a similar flow or dilution level each time.  Upstream inputs affect downstream estimates of eDNA concentration. 

Lentic systems or reservoirs require broad sampling rather than targeted locations of high density to estimate abundance without bias for the reservoir.  ​
   

A:  The meaning of the results depends on whether a person is monitoring for occurrence or for abundance.     

Monitoring Occurrence – Detecting occurrence of a species could indicate the presence of an aquatic nuisance species.  Unfortunately, sometimes a species is detected when it is not there (or false positives); or, it goes undetected when it really is there (or false negatives).  This  uncertainty should be addressed using a decision tree.  A decision tree must be created to resolve complex problems with a repeatable, easily understood solution.     

Uncertainty can also be addressed statistically using probability modeling, such as logistic regression that can partition variance to covariates that include environmental variables.    

An example of a decision tree is:   

1. Positive test?  Does it pass quality assurance tests?
   
1. No – false positive
2. Yes – are a priori criteria met for considering the site a positive?
1. No – false positive
2. Yes – Presumed positive site associated with a positive test from non-eDNA methods?
1. No – Does the non-eDNA method achieve an acceptable level of confidence in detection?
1. No – Presumed positive site
2. Yes – False positive inference
2. Yes – Confirmed positive site
   
   Monitoring Relative Abundance - For established aquatic nuisance species, it may be of interest to monitor changes in abundance over time.  This is an area of growing research and requires study to set appropriate expectations.  In practice, either the area under curves or the peak of the relationship of date (or time) to concentration of eDNA can be used to estimate abundance, and changes in area or peak reflect general trends in abundance.  Relative abundance or density can be corrected for bias owed to environmental variation using multiple regression models that partition variance in eDNA concentration to covariates such as environmental variables, similar to work commonly performed with catch-per-unit-effort data.  Unlike non-molecular field surveys, however, the basic unit of measure for eDNA monitoring of abundance is not a count of individual organisms.  Instead, eDNA is measured as a concentration and can be ranked to create an index of relative abundance.  For example: 
   
   Low (e.g., log₁₀ concentration of eDNA is 0 – 2)
   
   Moderate (e.g., log₁₀ concentration of eDNA is 2 – 3)

High (e.g., log₁₀ concentration of eDNA is 3 – 5)​
   

A:  Monitoring eDNA cannot be used to determine common biological aspects of interest to ANS scientists, including:  developmental stage, reproductive activity, fecundity, health, or physiology.  Also, eDNA monitoring should not be used if managers cannot decide upon a decision tree.  Detecting eDNA infers species presence, but inference implies uncertainty.  Uncertainty must be dealt with using a decision tree.  ​
   

A:  Yes, management agencies have successfully incorporated eDNA monitoring into ongoing surveys.  Field surveys and molecular, eDNA surveys share similar patterns when examined at broad spatial scales.  Monitoring with eDNA has been done for the following aquatic species:  round goby; Atlantic salmon; chinook salmon; eulachon; Pacific hake; zebra mussel ; northern snakehead; blue catfish; and hydrilla.  A positive, confirmed occurrence may trigger a Risk Assessment by management agencies and subsequent implementation of a Rapid Response Plan.  The Plan could include Structured Decision Making that uses outcome probabilities to increase odds of a good outcome.   

An example of Structured Decision Making is:     

1. Invite stakeholders
2. Determine all appropriate actions to take following a positive eDNA detection
3. Determine objectives for prevention (e.g., develop actions to confirm; do nothing; delay action; implement control)
4. Rank and weight objectives
5. Estimate likelihoods of outcomes based on objectives and uncertainty

Decide upon an objective and suite of actions based on likelihoods​
   

A:  Please search the library or www.scholar.google.com for the references below.   

Diana, A., E. Matechou, J.E. Griffin, A.S. Buxton, and R.A. Griffiths. 2021.  An RShiny app for modelling environmental DNA data: accounting for false positive and false negative observation errors. Ecography 44:1831-1844.   

Euclide, P.T., Y. Lor, M.J. Spear, T. Tajjioui, J.V. Zanden, W.A. Larson, and J.J. Amberg. 2021. Environmental DNA metabarcoding as a tool for biodiversity assessment and monitoring: reconstructing established fish communities of north-temperate lakes and rivers. Diversity and Distributions 27:1966-1980.   

Jo, T., K. Takao, and T. Minamoto. 2021. Linking the state of environmental DNA to its application for biomonitoring and stock assessment: Targeting mitochondrial/nuclear genes, and different DNA fragment lengths and particle sizes. Environmental DNA (https://doi.org/10.1002/edn3.253).   

Jo, T., S. Ikeda, A. Fukuoka, T. Inagawa, J. Okitsu, I. Katano, H. Doi, K. Nakai, H. Ichiyanagi, and T. Minamoto. 2021. Utility of environmental DNA analysis for effective monitoring of invasive fish species in reservoirs. Ecosphere 12:e03643.   

Muha, T.P., M. Rodríguez-Rey, M. Rolla, and E. Tricarico. 2017. Using environmental DNA to improve species distribution models for freshwater invaders. Frontiers in Ecology and Evolution 5:158.   

Schill, W.B. 2020. Capture of environmental DNA (eDNA) from water samples by flocculation. Journal of Visual Experimentation 159: e60967. Doi:10.379/60967.   

Schmidt, B.C., S.F. Spear, A. Tomi, and C.M. Bodinof Jachowski. 2021. Evaluating the efficacy of environmental DNA (eDNA) to detect an endangered freshwater mussel Lasmigona decorate (Bivalvia: Unionidae). Freshwater Science 40: 354.367.   

Sepulveda, A., P.R. Hutchins, M. Forstchen, M.N. Mckeefry, and A.M. Swigris. 2020. The elephant in the lab (and field): Contamination in aquatic environmental DNA studies.  Frontiers in Ecology and Evolution 8:440.   

Sepulveda, A.J., N.M. Nelson, C.L. Jerde, and G. Luikart. 2020. Are environmental DNA methods ready for aquatic invasive species management? Trends in Ecology and Evolution. 35:668-678.   

Tillotson, M.D., R.P. Kelly, J.J. Duda, M. Hoy, J. Kralj, and T.P. Quinn. 2018. Concentrations of environmental DNA (eDNA) reflect spawning salmon abundance at fine spatial and temporal scales. Biological Conservation 220: 1-11.   

Tingley, R., R. Coleman, N. Gecse, A. van Rooyen, and A.R. Weeks. 2020. Accounting for false positive detections in occupancy studies based on environmental DNA: A case study of a threatened freshwater fish (Galaxiella pusilla).  Environmental DNA 3:388-397.   

Yates, M.C., M.E. Cristescu, and A.M. Derry.  2021. Integrating physiology and environmental dynamics to operationalize environmental DNA (eDNA) as a means to monitor freshwater macro-organism abundance. Molecular Ecology 30:6531-6550.​