Lake Ecology

1
Lake Ecology

• Unit 1 Modules 2/3 Part 6 ManagementJanuary
  2004

2
Modules 2/3 overview

• Goal Provide a practical introduction to
  limnology
• Time required Two weeks of lecture (6 lectures)
  and 2 laboratories
• Extensions Additional material could be used to
  expand to 3 weeks. We realize that there are far
  more slides than can possibly be used in two
  weeks and some topics are covered in more depth
  than others. Teachers are expected to view them
  all and use what best suits their purposes.

3
Modules 2/3 outline

1. Introduction
2. Major groups of organisms metabolism
3. Basins and morphometry
4. Spatial and temporal variability basic physical
   and chemical patchiness (habitats)
5. Major ions and nutrients
6. Management eutrophication and water quality

4
6. Management topics

• Trophic status
• Eutrophication
• Water quality

5
Nutrients most limiting to algal growth

• Phosphorus
• Essential for growth
• PO4-3 is primary dissolved form
• PO4-3 sticks to soil and sediment particles
• Usually key nutrient for triggering excess plant
  growth
• Must be reduced to control eutrophication
• 1 lb (kg) P can yield 500 lbs (kg) fresh algae

• Nitrogen
• Essential for growth
• NO3-, NH4, and N2 are primary biological forms
• NO3- soluble in water
• May limit algal growth in some circumstances
• More difficult to remove from wastewater than P
• Some forms are toxic or disease-causing to fish
  and mammals (including humans)

6
Limiting nutrients demand versus supply

• Nitrogen and phosphorus are typically in
  extremely short supply in water relative to plant
  demand
• The Redfield ratio is the average composition
  of elements in phytoplankton
• Ratio 100DW40C7N1P

7
The concept of limiting nutrients

• Liebigs Law of the Minimum (1840)
• An organisms total biomass yield is proportional
  to the lowest concentration of nutrient relative
  to the requirements of that organism
  (paraphrased).
• Lake managers are interested in limiting
  nutrients because
• An increase might change water quality or food
  webs.
• Restoration often requires a strategy for
  reducing nutrient loading and predictions of the
  consequences of specific actions.

8
Limiting nutrients a conceptual example

• The following set of slides were developed to
  illustrate more specifically what is meant by
  limiting nutrients in the context of
  eutrophication studies
• This may be appropriate for a lab exercise in
  which different combinations of N and P are added
  to lake water
• Lake Superior was used as an example because we
  can see it out our window and because it is the
  biggest lake in the world and the cleanest of the
  Laurentian Great Lakes, so it is important to
  understand

9
Example loosely based on Lake Superior
10
Conceptual nutrient limitation bioassay 1

• This example is loosely based on Lake Superior
• 1. Algal composition is approximately
• 500 g wet weight 100 g dry weight 40 g C 7
  g N 1 g P

Remember that the ratio of CNP is called the
Redfield ratio and approximates the composition
of algae! 4071 by weight 100161 by atoms
11
Conceptual nutrient limitation bioassay 2

• 2. Mid-summer bioavailable water chemistry
• Dissolved inorganic carbon (DIC)
• 10,000 µg C/L (as carbon dioxide and
  bicarbonate)
• Dissolved inorganic nitrogen (DIN)
• 300 µg N/L (95 as nitrate, with very low
  ammonium)
• Dissoved inorganic phosphorus (ortho-P, DIP)
  0.5 µg P/L

12
Conceptual nutrient limitation bioassay 3

• 3. Assume
• Algal biomass B0 200 µg C/L (particulate)
• Algal maximum growth rate 20 per day

13
Conceptual nutrient limitation bioassay 4

• 4. Run a nutrient enrichment experiment to
  estimate the limiting nutrient by doubling each
  nutrient
• Set up 4 liter bottles of lake water in
  triplicate
• Incubate for 1 day and re-measure algal biomass
  (Bf)

14
Conceptual nutrient limitation bioassay 5

• 5. What happens?
• After 1 day algae grow 20 X 200 µg C/L 40
  µg C/L
• Apply the Redfield Ratio to estimate nutrient
  needs

• Is there sufficient DIC to support this much
  growth?
• Is there sufficient DIN to support this much
  growth?
• Is there sufficient DIP to support this much
  growth?

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Conceptual nutrient limitation bioassay 6

• 6. What happened?
• 40 µg C/L of new growth would require
• 40 µg DIC/L 7 µg DIN/L 1 µg DIP/L

• 0 control treatment
• 10,000 µg DIC/L is much more than enough
• 300 µg DIN/L is more than enough (293 excess)
• 0.5 µg DIP/L is half of what is needed
• Therefore growth is 50 of maximum
• 20 µg C/L

16
Conceptual nutrient limitation bioassay 6

• 6. What happened?
• 40 µg C/L of new growth would require
• 40 µg DIC/L 7 µg DIN/L 1 µg DIP/L

• N treatment
• 10,000 µg DIC/L is much more than enough
• 600 µg DIN/L is more than enough (593 excess)
• 0.5 µg DIP/L is half of what is needed
• Therefore growth is 50 of maximum
• 20 µg C/L

17
Conceptual nutrient limitation bioassay 6

• 6. What happened?
• 40 µg C/L of new growth would require
• 40 µg DIC/L 7 µg DIN/L 1 µg DIP/L

• C treatment
• 20,000 µg DIC/L is much more than enough
• 300 µg DIN/L is more than enough (293 excess)
• 0.5 µg DIP/L is half of what is needed
• Therefore growth is 50 of maximum
• 20 µg C/L

18
Conceptual nutrient limitation bioassay 6

• 6. What happened?
• 40 µg C/L of new growth would require
• 40 µg DIC/L 7 µg DIN/L 1 µg DIP/L

• P treatment
• 10,000 µg DIC/L is much more than enough
• 300 µg DIN/L is more than enough (293 excess)
• 1.0 µg DIP/L is just what is needed
• Therefore growth is 100 of maximum
• 40 µg C/L

19
Nutrient bioassay summary and plot

• An enrichment of only 0.5 µg P/L doubled algal
  growth
• It would take a depletion of 43 µg P/L to deplete
  the 300ug DIN/L, based on the 71 ratio
• The DIC is virtually inexhaustible in all lakes.
  
• It may briefly limit algal growth in
  hypereutrophic sewage oxidation ponds
• The data suggest strong P-limitation for Lake
  Superior

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Nutrient limitation bioassay responses

• In progress, 10/20/03

21
Halsteds Bay late summer mixing events

• What might this mean for phosphorus levels in the
  water column?
• Why?

22
Medicine Lake Algal blooms mixing events - 1

• Background
• Medicine Lake is extremely productive because of
  historically high nutrient enrichment from its
  watershed
• (go to http//lakeaccess.org/lakedata/lawnfertiliz
  er/mainlawn.htm)
• Major blooms of algae can be detected in the
  RUSS data set as
• supersaturated O2 (why ?)
• increased pH (why ?)
• increased chlorophyll-a or turbidity (why ?)

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Medicine Lake Algal blooms mixing events-2
Color O2 Line pH
STRATIFY
RE- STRATIFY
MIX
MIX
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Halsteds Bay Algal blooms mixing events- 3
Why did the phosphorus in the bottom water drop
so dramatically in August 1999 in Halsteds Bay ?
P levels drop
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Halsteds Bay Algal blooms mixing events- 4

• First, focus on the ice-free season water quality
• relatively high epilimnion (surface)TP 75-150
  ugP/L
• chlor-a (algae ) builds up steadily to levels gt
  50 ug/L

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Halsteds Bay Algal blooms mixing events- 5
See how secchi drops as chlorophyll increases ?

27
Halsteds Bay Algal blooms mixing events- 6
Now see how much TP is in the hypolimnion
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Halsteds Bay Algal blooms mixing events- 7
Summary slide without animation
29
Medicine Lake Storm mixing events

• This sequence runs from 1-5 from Aug 29-30, 1999

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Trophic status classification

• This topic will be developed further in Module
  22 (Regulations and Compliance Monitoring - Lake
  Biocriteria)
• Managers need to classify lakes to set water
  quality standards and prioritize monitoring,
  research, and restoration .
• Lake productivity, as indicated by its
  production of algal biomass, is a useful
  classification in regard to water quality issues
  as well as fisheries management
• Trophic status indices usually assume that
  nutrient levels (e.g. total-P) control algal
  biomass (measured by chlorophyll-a) which in turn
  regulates lake clarity (Secchi disk transparency)

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Trophic Status

• Carlson trophic state index (TSI)- most widely
  used
• based on log transformation of Secchi disk
  values as a measure of algal biomass on a scale
  from 0 110
• 10 units doubling of algal biomass
• TSIs also developed for chlor-a and total-P
  based on their relationships to secchi for a set
  of midwestern lakes
• TSI useful for comparing lakes within a region
  and for assessing changes in trophic status over
  time
• Time period usually summer often set at June
  15 Sep 15 but it is rarely a good idea to
  restrict data acquisition without a good reason
  especially Volunteer secchi data

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Carlson TSI equations

• TSI-S 60 - 14.41 ln Secchi disk, m
• TSI-C 9.81 ln Chlor-a, µg/L 30.6
• TSI-P 14.42 ln TP, µg/L 4.15
• Average TSI TSI-P TSI-C TSI-S / 3
• If the 3 TSI values are not similar to each
  other, it is likely that
• algae may be light- or nitrogen-limited instead
  of P-limited, or
• secchi is affected by erosional silt rather than
  by algae, or something else. One should look
  deeper into the data!
• Note that Dr. Carlson recommended not averaging
  the 3 values to avoid obscuring important
  differences

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Carlson TSI vs water quality
lt40 Oligotrophic clear water high hypolimnetic O2 year-round but possible anoxia in the deeper hypolimnion part of year
40-50 Mesotrophic moderately clear water possible hypolimnetic anoxia in summer and/or under ice. Fully supportive of all swimmable /aesthetic uses possible cold-water fishery
50-60 Mildly eutrophic decreased secchi anoxic hypolimnion possible macrophyte problems warm-water fishery supportive of all swimmable /aesthetic uses but threatened
60-70 blue-green algal dominance with scums possible extensive macrophyte problems not supportive of all beneficial uses
gt70 Heavy blooms and scums in summer likely dense weed beds hypereutrophic possible fish kills fewer plant beds due to high algae not supportive of many beneficial uses
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TSI (Carlson) - graphical
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What are Ecoregions ?

• Areas with similar
• Climate
• Landuse
• Soils
• Topography
• Potential natural vegetation
• Minnesota has seven major ecoregions
• Four ecoregions contain most of the lakes
• Water quality varies greatly from south to north

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Minnesotas Ecoregions
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1.6-3.3 ft
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Comparison of trophic indicators in Minnesota
TP (ug/L) TP (ug/L) TP (ug/L) Chlor-a (ug/L) Chlor-a (ug/L) Chlor-a (ug/L) Secchi (m) Secchi (m) Secchi (m) TSI (Carlson) TSI (Carlson) TSI (Carlson)
Trophic Status O M E O M E O M E O M E
Standard Criteria lt11 11- 24 gt24 lt3 3- 7 gt7 gt4.0 4.0- 2.2 lt2.2 lt35 40-55 gt55
NLF 14 - 27 14 - 27 14 - 27 lt 10 lt 10 lt 10 2.4 - 4.6 2.4 - 4.6 2.4 - 4.6 41 - 52 41 - 52 41 - 52
NCHF 23-50 23-50 23-50 5 - 22 5 - 22 5 - 22 1.5 3.2 1.5 3.2 1.5 3.2 49 - 66 49 - 66 49 - 66
WCB 65 - 150 65 - 150 65 - 150 30 - 80 30 - 80 30 - 80 0.5 1.0 0.5 1.0 0.5 1.0 67 - 77 67 - 77 67 - 77
NGP 130 - 250 130 - 250 130 - 250 30 - 55 30 - 55 30 - 55 0.3 1.0 0.3 1.0 0.3 1.0 67 - 73 67 - 73 67 - 73
O oligotrophic M mesotrophic E eutrophic see slide notes and accompanying slide for Minnesota Ecoregions map and code names General values from Axler et al. 1994. O oligotrophic M mesotrophic E eutrophic see slide notes and accompanying slide for Minnesota Ecoregions map and code names General values from Axler et al. 1994. O oligotrophic M mesotrophic E eutrophic see slide notes and accompanying slide for Minnesota Ecoregions map and code names General values from Axler et al. 1994. O oligotrophic M mesotrophic E eutrophic see slide notes and accompanying slide for Minnesota Ecoregions map and code names General values from Axler et al. 1994. O oligotrophic M mesotrophic E eutrophic see slide notes and accompanying slide for Minnesota Ecoregions map and code names General values from Axler et al. 1994. O oligotrophic M mesotrophic E eutrophic see slide notes and accompanying slide for Minnesota Ecoregions map and code names General values from Axler et al. 1994. O oligotrophic M mesotrophic E eutrophic see slide notes and accompanying slide for Minnesota Ecoregions map and code names General values from Axler et al. 1994. O oligotrophic M mesotrophic E eutrophic see slide notes and accompanying slide for Minnesota Ecoregions map and code names General values from Axler et al. 1994. O oligotrophic M mesotrophic E eutrophic see slide notes and accompanying slide for Minnesota Ecoregions map and code names General values from Axler et al. 1994. O oligotrophic M mesotrophic E eutrophic see slide notes and accompanying slide for Minnesota Ecoregions map and code names General values from Axler et al. 1994. O oligotrophic M mesotrophic E eutrophic see slide notes and accompanying slide for Minnesota Ecoregions map and code names General values from Axler et al. 1994. O oligotrophic M mesotrophic E eutrophic see slide notes and accompanying slide for Minnesota Ecoregions map and code names General values from Axler et al. 1994. O oligotrophic M mesotrophic E eutrophic see slide notes and accompanying slide for Minnesota Ecoregions map and code names General values from Axler et al. 1994.
39
TSI Trends in Minneapolis, MN area WOW Lakes
Note importance of flagging which TSI is plotted
and leaving space for missing years
Solid barsTSI average for TP, chlor and secchi
striped secchi only
How would you determine how well the TSI- secchi
alone (stripes) predicts average TSI or TSI-
chlor ?
40
Chlor-a - TP and Secchi TP relationships in MN
Notice that lake clarity is much more
sensitive to increased phosphorus at the low end
of the scale. Why ?
Data from Minnesota Pollution Control Agency Year
2000 Lake Assessment report (www.pca.state.mn.us)
41
Ex Halsteds Bay late summer mixing events

• Run the color mapper from April 1999 through 2002
  focusing on storm events in mid August 1999 and
  2000
• START with MAP TEMP and plot DO to show
  variable stratification
• Then switch to MAP DO and PLOT TEMP to show
  anoxic events and discuss the release of P from
  sediments that swamps annual P-inflow from the
  watershed

42
Hypolimnion responses to increasing productivity
Trophic Status O2 PO4-3 NH4 H2S Fe2 (ferrous)
Oligotrophic High (mostly) Low Low Absent Absent
Mesotrophic Low partly anoxic Low High if anoxic Moderate High if anoxic Absent Present where anoxic
Eutrophic Anoxic High High High High
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Hypolimnion responses to anoxia

• As the hypolimnion becomes O2 depleted
• NH4 accumulates
• increased organic matter is decomposing
• cannot be converted to NO3- without 2
  (bacterial nitrification)
• not much algal uptake (its dark and anoxic)
• Insoluble oxidized Fe3 (ferric) at sediment
  surface is reduced to Fe 2 (ferrous) that is
  soluble the phosphate adsorbing layer dissolves
• PO4-3 diffusion from the sediments increases
  dramatically
• Increasing decomposition leads to strong
  reducing conditions that favor bacterial
  reduction of sulfate to sulfide - producing
  rotten egg gas (H2S)
• Mixing adds lots of available N P to the
  sunlit zone ALGAE !!

44
Eutrophication and water quality
45
Trophic (feeding metabolism) terminology
Oligotrophic low nutrients and productivity
usually high clarity
Mesotrophic moderate nutrients, productivity
and clarity
Eutrophic high nutrients and productivity
low clarity
46
Eutrophication Excess fertility leading to
excessive plant growth
47
Water Quality Impacts- Eutrophication (some of
them)

• excess algae scums, noxious blue-greens,
  taste/odor/smell

• O2 depletion loss of fish habitat

• loss of clarity (secchi depth) aesthetic loss

• excess macrophyte (weed) growth- loss of open
  water favors exotic species (EWM) sediment
  destabilization

• game fish impacts

48
Water Quality Impacts- Eutrophication (and some
more)

• loss of native macrophytes from algal shading
  loss of fish waterfowl habitat and food
  reduced shoreline bottom stabilization,
  increased erosion

• lower bottom O2 increased sediment nutrient
  release loss of fish habitat

• excess organic matter smothers eggs and bugs

49
Eutrophication natural vs cultural

• Natural filling by mineral and organic sediment
  leads to lower V and larger AwA0 and A0V
• Lake to wetland conversion
• Time scale gt 103 years (if at all)
• Irreversible

• Human-caused from excess nutrient inputs and poor
  land-use management
• Water quality degraded loss of beneficial uses
• Time scale lt decades
• Reversible loading

50
Eutrophication the sad Lake Tahoe story
Data courtesy of C.R. goldman and J.E. Reuter,
Tahoe Reesrach Group, U. of California-Davis,
http//www.news.ucdavis.edu/tahoetv/
51
Other regulators of lake productivity - Grazing

• Top-down Model
• High rates of nutrient driven algal growth is
  removed by intense zooplankton grazing pressure
  (usually cladoceran Daphnids)
• Fishless lakes with low zooplankton predation
• Lakes where planktivorous fish are regulated by
  predatory fish (game fish) usually by intensive
  control
• In these cases, algae are not nutrient limited
• management tool biomanipulation

• Bottom-up Model
• Nutrient inputs drive algal growth
• Classic Pyramid

52
Potential Top-down effects on food chains
Low Predators
HIGH Predators
HIGH Planktivores
Low Planktivores
HIGH Zoops
Low Zoops
Smaller Zoops less grazing
Larger Zoops more grazing


HIGH Algae
Low Secchi O2 stress high pH ??
Low Algae
Higher Secchi less O2 stress lower pH ??
53
Biomanipulation fish management

• Fish control
• Intensive netting
• Rotenone (poison)
• Stock increased s of piscivorous fish
• Selective catch or catch restrictions
• Control conditions for fish and zoop growth and
  survival

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Biomanipulation- Summary

• Summary
• Considered experimental
• Requires complex knowledge of food web processes
  (shallow lakes are particularly poorly
  understood)
• Herbivores may not consume certain blue-greens
• May be more successful in lakes without
  large-bodied zooplankton
• May require external loading to also be
  controlled
• Currently considered only a management tool- not
  a restoration technique

55
Lake Mendota Biomanipulation Project

• Lake Mendota large, urban, limnologically
  famous lake in Madison, WI
• Eutrophic with blooms of blue-green algae
• Sewage effluents diverted out of basin entirely
  by 1971
• Continued nonpoint pollution from agricultural
  and urban runoff
• 1987 attempt to control blooms by a massive
  stocking of walleye to reduce planktivorous fish

• 1988 hot summer causes summerkill of Ciscos,
  the major planktivore
• zoops increase and algae decrease for few years
• Ciscos recover, anglers hammer the walleye,
  zoops decrease and algae are back

56
Other lake productivity regulators light shading

• Nutrients arent always the whole story
• Shallow lake research
• Aquatic plants vs algae
• Over a wide range of nutrients there are
  alternative stable states of dominance
• Plants shade phytoplankton creating clearwater
• Phytoplankton turbidity shades plants and
  restricts growth to nearshore
• Periphyton mats and mucky sediments hinder plant
  rooting
• High densities of grazers regulate periphyton on
  leaves

57
Water transparency clear vs turbid state
Water transparency clear vs turbid state
58
Water transparency clear vs turbid state -2
Water transparency clear vs turbid state -2
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Shallow lakes vs deeper lakes - switches

• Usually more productive higher AwAo ratio
• Plants vs algae
• Natural predominance of macrophytes over algae.
  Human impacts can switch them from
  clearwater-plants to turbid water-algae state
  maintained by
• Poor fish management (carp, exotics, )
• Inadequate shoreline protection of emergent veg
• Boat damage
• Pesticide and nutrient runoff (fish, grazers,
  plants)
• Susceptible to very obnoxious algal blooms
• Difficult to reestablish clearwater-macrophyte
  state

60
Photosynthesis (PPr) respiration (Rn) effects
on routine water quality parameters examples
Temperature no effect generally. High rates of
respiration can increase the temperature in
bottom waters over long periods of time
(gtdecades) but this is unusual and associated
with meromixis DO High rates of photosynthesis
( primary productivity PPr) produce O2 and can
lead to supersaturation (gt100) EC25 EC
increases in the hypolimnion during stratified
periods due to mostly to the accumulation of
bicarbonate ions (HCO3- ) from respired CO2 that
dissolves in the water at moderate pH (6-9). The
pH is usually lowered as well. pH High rates of
PPr increase pH due to the removal of CO2 and
HCO3- from the water (essentially removing
carbonic acid) repiration does the opposite as
noted above for EC25.
61
PPr Rn effects in relation to density layering

• The line plots are dissolved-O2

62
More about Onondaga in 2003
Heres DO

• DO gt 150 from 0-3m and then lt10 down to the
  bottom !
• pH drops gt1 unit from 3 down to 5 m
• EC jumps up and down by 400 uS/cm !

63
Lake Washington tidbits Apr- Oct 2002
Apr high chlor Is it real ?
Sep low chlorophyll low metalimnion DO - Is
it real ?
Oct high chlorophyll - Is it real ?
64
Water Quality What is it ?

• Water quality is actually a subjective term that
  is used to describe the condition of a water body
  in relation to
• the needs of humans (beneficial uses in
  regulatory parlance),
• or the needs of aquatic organisms
• Water quality is not an absolute since different
  user groups may have different expectations and
  values
• Water quality protection involves both human
  health and environmental health risk assessments
  and management
• Water quality regulatory standards alone may be
  met yet the patient may die. For this reason
  biocriteria have become an important new aspect
  of water resource protection

65
Water Quality Whats a high value ?

• Protection environmental health vs human health
• Beneficial use fishable swimmable vs drinkable
• Lake-P 100 ppb hyper-eutrophic
• Cola-P 1000's ppb tasty
• Drinking water-P no limit (Duluth adds 1000 ppb
  to control lead leaching from old pipes)
• Lake-N gt500 ppb high
• Drinking water OK if lt 10,000 ppb Nitrate-N
• Lake Hg lt 3 ppt vs DW lt 2,000,000 ppt
• Lake fish PCBslt 50 ppb vs Baby food lt 2000 ppb

66
Water quality depends on many factors

• Characteristics of the ecoregion
• Type and size of the watershed
• Precipitation patterns and surface water
  hydrology
• Groundwater influences
• Lake size, shape, and retention time
• Number of people and land uses in the watershed

67
Minnesota Ecoregions
68
1.6-3.3 ft
69
Other important factors affecting the health and
economic sustainability of lake resources

• Non-water quality impacts
• shoreline attached algae aquatic plants
• shoreline woody debris aquatic habitat
• exotic species (invasive plants animals)
• noise pollution
• light pollution
• sight pollution

70
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