Incorporating Data Logger and Biological Monitoring to Diagnose Stream Pollutants

and Aid in Reclamation Efforts

By Eric NullAquatic Biologist

Conemaugh Valley Conservancy

Data Logger and Biological Monitoring

• Two Very Powerful Tools for Pollution Monitoring

• Biological Sciences and Data Logging Technology are Advancing Rapidly

• Both are Long Term Monitoring Practices • When Used Together They can Produce

Powerful Data

An Introduction on How to Drill Into the Data

Data Logger Data

The Unique Qualities of Data Logger Data

• Data Logger Data Sets are Immense • Logging Intervals Must Be Short To Capture

Episodes (15 min)• This Data can not be Looked at Like Grab Data • Averages Change Drastically • Full Stream Behavior is Seen • Eyes Going Crossed and Migraines are

Symptoms

Every Stream is Different

Spikes and Valleys

• Can be Caused Naturally or by Disturbance • Frequency and Duration can Determine

Between Causes

Stream A

Stream B

Biological Data

Macroinvertebrates

• Macroinvertebrate Taxa Act Like Letters in the Alphabet that can Spell Out Pollutants

• Certain Taxa only Thrive in Certain Polluted Conditions

• Abundance and Diversity Can Determine the Type of Pollutant

Spelling Test

• Your Stream is Dominated by the following Taxa, What is the Pollutant ?– Amphinemura– Cheumatopshche – Ilybius – Diptera – ACID Impacts

Another Stream

• Your Stream is Dominated by the following Taxa, What is the Pollutant ?– Hydropsyche – Odonates – Tabanus – This Stream has Thermal Pollution, It is HOT

One More

• Take a Guess what is Wrong Here – Psilotreta – Oligochaeta – Ochlerotatus– You guessed it Organics and Sewage

Fish Data

• Fish Abundance and Diversity can Determine Pollution

• Fish Disappear Before Macroinvertebrates in Polluted Streams

• Different Fish Life Stages are impacted by Different Pollutants

Cross Referencing Biological and Data Logger Data to Diagnose the Pollutant • This is When Both Make More Sense • Conductivity and Other Parameters Influence

Community Structure • The Community Structure Indicates What is

causing the Conductivity and Other Parameters to Behave the way they are Behaving

Stream A

Logger Data Biological Data • Macroinvertebrates

– Extremely Low Numbers of Individuals

– Poor Diversity – Acid Tolerant Taxa

• Fish – All Juveniles – Low Numbers of

Individuals – Ok Diversity

Stream A

• Pulsing Spikes with a Constant Occurrence• Depressed Biological Communities • No Adult Fish • Pollution Tolerant Macroinvertebrates • ACID and METALS

Stream B

Data Logger Data Biological Data • Macroinvertebrates

– High Biomass and Individuals

– Low Diversity – Organic and Acid

Tolerant Black Fly Taxa were Dominant

– Most Taxa Collected were Pollution Tolerant

Stream B

• Large Conductivity Spikes • High Biomass and Abundance • Low Diversity of Macros • Acidophilic Macroinvertebrates • ORGANICS AND ACID

Stream C (The Hard One)

Data Logger Data Biological Data • Macroinvertebrates

– Low Diversity and Numbers

– Acid Tolerant Taxa

• Fish– Low Diversity – Acid Tolerant Taxa – White Sucker/Creek

Chub

Stream C

• Consistent Mid Level Conductivity • Low Macroinvertebrate Diversity and

Abundance • Low Fish Abundance and Diversity • Pollution Tolerant Taxa (Fish and Macros)• Episodic Acidification with Alkalinity

Replacement by Metals and Acidity

Stream D

Data Logger Data Biological Data • Macroinvertebrate

– Very High Diversity – Very High

Abundance – Dominated by

Pollution Intolerant Taxa

– No Organic Loading

Stream D

• Very Consistent and Low Conductivity • Very Diverse Macroinvertebrate Community • Volunteers and Staff Very Excited to

Electrofish in 2015 • HIGH QUALITY H2O

Conclusions

• Data Logger and Biological Data on their Own are Powerful Assessment Tools

• When Combined they can be used Very Effectively to Isolate Individual Pollutants

• Data Sets May Appear Confusing at First, but Over Time Become Easier to Interpret

• Using Both can Better Interpret Each Individual Data Set

Questions?