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IMPACTS  OF  AGRICULTURAL  LAND  USE  CHANGE  ON  FISH  AND  AQUATIC  

MACROINVERTEBRATE  ASSEMBLAGES  IN  THE  NOLICHUCKY  RIVER  WATERSHED  

Hayley  Gotwald  M.S.  Student  

Department  of  Forestry,  Wildlife,  and  Fisheries  28  October  2015  –  12:20  PM  –  PBB  160  

 

IntroducVon  

JusVficaVon  

Research  ObjecVves  

Proposed  Methods  and  Analysis  

Outline  

The  Clean  Water  Act    

Copeland  2008  

But  only  offers  monetary  incenVves  to  prevent  nonpoint  source  polluVon  

Regulates  point  source  polluVon  

through  permi]ng  

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Results  from  land  runoff  transporVng  pollutants  

Nonpoint  Source  PolluVon  

EPA  2012;  2015  

16%  

15%  

11%  10%  7%  

Agriculture:  #1  reason  for  impairment  

Unknown  

Atmospheric  DeposiVon  

HydromodificaVon  

Habitat  AlteraVon  

Water  Quality  in  TN  

52%  48%  

EPA  2012;  TDEC  2014  

1st   Grazing  In  Riparian  Or  Shoreline  Zones   Agriculture  

2nd   ChannelizaKon   HydromodificaKon  

3rd   Non-‐Irrigated  Crop  ProducKon   Agriculture  

4th  Discharges  From  

Municipal  Separate  Storm  Sewer  Systems  

Urban-‐Related  Runoff/Stormwater  

5th  Site  Clearance  (Land  Development  Or  Redevelopment)  

ConstrucKon  

Impaired  

Not  Impaired  

TDEC  2008;  Jackson  2009  

Agricultural  land  use  47%  on  TN  side  of  the  watershed    

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Agriculture  in  the  Nolichucky  Watershed  

ObjecVves  

1.   QuanVfy  changes  in  overall  land  use  and,  more  specifically,  row  crop  cover  in  the  Nolichucky  River  watershed  from  2000  to  present,  and  predict  how  land  use  and  row  crop  coverage  will  change  in  the  future.  

2.   Correlate  bioVc  condiVon  to  land  use  acributes  to  determine  those  that  may  be  considered  indirect  stressors  that  ulVmately  lead  to  degraded  stream  fish  and  invertebrate  assemblages.  

ObjecVves  

3.   IdenVfy  fish  and  macroinvertebrate  species  that  may  serve  as  indicator  species  of  land  use  stressors  in  the  Nolichucky  River  watershed.  

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Methods  

0 10 20 30 405Kilometers

Remotely  Sensed  Data  

USGS  2015  and  2014;  NAIP  2014  

ResoluVon  

Sensor   Temporal   SpaVal   Spectral  

Satellite  Images   Landsat  7  and  8   16  days   30  m  x  30  m   8  to  11  bands  

Aerial  Photos   NAIP;  Google  Earth   Yearly   1  m  x  1  m   3  bands  

Land  Use  Types  

1  

2  

3  

4  

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Land  Use  Classifica.on  Workflow

Satellite  Images  

Aerial  Photos  

Radiometric  CorrecVon  

Atmospheric  CorrecVon  

Create  172  Random  Points  

Classify  Points  into  Land  Use  Types  

Use  80%  of  Points  to  Create  Land  Use  Maps  

Use  Remaining  20%  of  Points  to  Assess  Accuracy  

Congalton  and  Green  2009  

IBI  Methods  

Jowea  1993  

RIFFLE  

RUN  

POOL  SHORELINE  

FFish  IBI  

TVA  2004  

Riffle  and  Run   Shoreline  

Pool  

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Benthic  Macroinvertebrate  IBI  

TDEC  2011  

•  One  sample  in  “fast”  riffle  and  one  in  a  “slow”  riffle  

•  500  micron  mesh  kick  net  

Benthic  Macroinvertebrate  IBI  

TDEC  2011  

StaVsVcal  Analysis  

ObjecVve  1:  QuanVfy  land  use  types  and  predict  change  

•  QuanVfy  land  cover  with  supervised  classificaVon  with  training  samples  created  by  the  172  points  into  land  cover  types  on  aerial  photos  

•  To  predict  Change:  Markov  Chain  Model  

Weng  2002;  Modal  et  al.  2013;  Corner  et  al.  2014  

   

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StaVsVcal  Analysis  

ObjecVve  2:  Correlate  bioVc  condiVon  to  land  use    •  Use  Soil  and  Water  Assessment  Tool  to  quanVfy  amount  of  

pollutants  washed  off  crop  fields  

•  General  addiVve  model  (GAM)  –  to  find  at  what  percentage  row  crops  negaVvely  affect  IBI  metrics  

•  Canonical  Correspondence  Analysis  (CCA)  –  to  find  the  degree  to  which  IBI  metrics  vary  with  changing  amounts  of  land  use  

McCune  and  Grace  2002  

StaVsVcal  Analysis  

ObjecVve  3:  IdenVfy  species  that  may  serve  as  indicator  species  of  polluVon  from  row  crops    •  Indicator  species  analysis    

McCune  and  Grace  2002  

Conclusion  

Unmanaged  nonpoint  source  polluVon  can  negaVvely  impact  stream  inhabitants  and  water  quality.  

 My  research  will  help  becer  understand  how  nonpoint  source  polluVon  from  agriculture  can  affect  biodiversity  

in  the  Nolichucky  River  watershed.  

McCune  and  Grace  2002  

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Photo  Sources  •  haps://www.flickr.com/photos/alan-‐swif348/  •  haps://upload.wikimedia.org/wikipedia/commons/9/95/Runoff_of_soil_%26_ferKlizer.jpg  •  hap://tdeconline.tn.gov/dwrwqa/  •  hap://smoothingit.com/2013/03/21/canoeing-‐the-‐shenandoah-‐river/  •  ArcMap  •  hap://www.thegeofactor.com/a-‐new-‐look-‐at-‐the-‐earth-‐landsat-‐8-‐launches/  •  hap://www.appliedeco.com/images/AES%20PLANE.jpg  •  hap://www.satelliteimpressions.com/landsat.html  •  hap://www.njflyfishing.com/vBulleKn/aaachments/f5-‐north-‐eastern-‐general-‐discussion-‐forum/

9115d1367411414-‐whats-‐difference-‐between-‐riffle-‐pocket-‐water-‐anatomy-‐stream.jpg  

•  hap://www.cliparthut.com/clip-‐arts/1759/trout-‐clip-‐art-‐black-‐and-‐white-‐1759817.png  •  hap://www.pugetsoundstreambenthos.org/  •  hap://www.toddamacker.com/  •  hap://tn.water.usgs.gov/lten/gallery2.html  •  hap://aquaKcinsectsofcentralvirginia.blogspot.com/2015/08/the-‐best-‐of-‐best-‐looking-‐at-‐

photos.html  

•  haps://www.flickr.com/photos/janhamrsky/  •  hap://lifeinfreshwater.net/  

CitaVons  •  Congalton,  R.  G.,  and  K.  Green.  2009.  Assessing  the  accuracy  of  remotely  sensed  data.  CRC  Press,  

Boca  Raton,  Florida.  

•  Copeland,  C.  2008.  Clean  water  act:  a  summary  of  the  law.  U.S.  Congressional  Research  Service.  Report  number:  RL30030.    Available  from:  HeinOnline.  

•  Corner,  R.  J.,  A.  M.  Dewan,  and  S.  Chakma.  2014.  Monitoring  and  predicKon  of  Land-‐Use  and  Land-‐Cover  (LULC)  Change.  GeospaKal  PerspecKves  on  UrbanisaKon,  Environment,  and  Health.  pp  75-‐97.  

•  EPA.  2012.  What  is  nonpoint  source  polluKon?  Environmental  ProtecKon  Agency.    

•  EPA.  2015.  NaKonal  summary  of  state  informaKon.  Environmental  ProtecKon  Agency.    

•  Hatch,  D.,  K.  Goulding,  and  D.  Murphy.  2002.  Nitrogen.  Pages  7-‐25  in  P.  M.  Haygarth  and  S.  C.  Jarvis,  editors.  Agriculture,  hydrology,  and  water  quality.  CABI  Publishing,  New  York,  New  York.  

•  Gevao,  B,  and  K.  C.  Jones.  2002.  PesKcides  and  persistent  organic  pollutants.  Pages  83-‐100  in  P.  M.  Haygarth  and  S.  C.  Jarvis,  editors.  Agriculture,  hydrology,  and  water  quality.  CABI  Publishing,  New  York,  New  York.    

•  TDEC.  2008.    Nolichucky  River  Watershed  of  the  Tennessee  River  Basin:  Watershed  Water  Quality  Management  Plan.    Tennessee  Department  of  Environment  and  ConservaKon,  Division  of  Water  PolluKon  Control,  Watershed  Management  SecKon.  Nashville,  TN.  63pp.  

•  Jackson,  G.  2009,  September  14.  Update:  Washington  county  Tennessee  residents  concerned  about  large  fish  kill.  The  Bristol  Herald  Courier.  Retrieved  from  hap://www.triciKes.com    

CitaVons  •  Jowea,  I.  G.  1993.  A  method  for  objecKvely  idenKfying  pool,  run,  and  riffle  habitats  from  physical  

measurements.  New  Zealand  Journal  of  Marine  and  Freshwater  Research  27(2):  241-‐248.  

•  McCune,  B.,  and  J.  B.  Grace.  2002.  Analysis  of  ecological  communiKes.  Gleneden  Beach,OR:  MjM  Sofware  Design.    

•  Modal,  M.  S.,  N.  Sharma,  M.  Kappas,  and  P.  K.  Garg.  2013.  Modeling  of  spaKo-‐temporal  dynamics  of  land  use  and  land  cover  in  a  part  of  Brahmaputra  River  basin  using  GeoinformaKc  techniques.  Geocarto  InternaKonal  28(7):  632-‐656.  

•  TDEC.  2011.  Quality  system  standard  operaKon  procedure  for  macroinvertebrate  stream  surveys.  Tennessee  Department  of  Environment  and  ConservaKon,  Division  of  Water  PolluKon  Control.  Nashville,  TN.  214  pp.  

•  TVA.  2004.  TVA  Protocol  for  ConducKng  an  Index  of  BioKc  Integrity  Biological  Assessment.  Tennessee  Valley  Authority.  Knoxville,  TN.  15pp  

•  USGS.  2015.  Landsat  Missions  Timeline.    United  States  Geological  Survey    

•  USGS.  2014.  Frequently  Asked  QuesKons  About  the  Landsat  Missions.  United  States  Geological  Survey.    

•  Weng,  Q.  2002.  Land  Use  Change  Analysis  in  the  Zhujiang  Delta  of  China  Using  Satellite  Remote  Sensing,  GIS  and  StochasKc  Modeling.  Journal  of  Environmental  Management    64(3):273-‐284.  

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Acknowledgements  

Adviser  &  Commiaee  Members  Dr.  Brian  Alford  Dr.  Robert  Washington-‐Allen  Dr.  Andrea  Ludwig  

Lab  Members  Joyce  Coombs  JusKn  Wolbert  Keith  Garner  Dan  Walker  Todd  Amacker  

Funding  Sources  

Sources  QuesVons?  

Hayley  Gotwald  hgotwald@vols.utk.edu