PPT - College of Natural Resources, UC Berkeley

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Transcript PPT - College of Natural Resources, UC Berkeley

Biomonitoring and
assessment
Why?
Demand Continues to Increase
but we’re reaching a limit
Ecological Society of America
Sadly more why
“One child dies every 15 seconds
from the lack of clean freshwater”
(> 2,000,000/year)
Along with Silent Spring etc.
http://www.cwru.edu/artsci/engl/marling/60s/pages/richoux/Photographs.html
Clean Water Act (1972)
Still an emphasis on chemistry
A Better Balance
Between Chemistry, Biology, and Physical Habitat
For many years following the passage of CWA in 1972, EPA, states, and
Indian tribes focused mainly on the chemical aspects of the "integrity"
goal. During the last decade, however, more attention has been given to
physical and biological integrity. Also, in the early decades of the Act's
implementation, efforts focused on regulating discharges from traditional "point
source" facilities, such as municipal sewage plants and industrial facilities, with
little attention paid to runoff from streets, construction sites, farms, and other
"wet-weather" sources.
Additionally, increasing emphasis on “nonpoint”
Starting in the late 1980s, efforts to address polluted runoff have increased
significantly. For "nonpoint" runoff, voluntary programs, including cost-sharing
with landowners are the key tool. For "wet weather point sources" like urban storm
sewer systems and construction sites, a regulatory approach is being employed.
http://www.epa.gov/watertrain/cwa/
The Clean Water Act
FEDERAL WATER POLLUTION CONTROL ACT
[As Amended Through P.L. 107–303, November 27, 2002]
FEDERAL WATER POLLUTION CONTROL ACT
(33 U.S.C. 1251 et seq.)
AN ACT To provide for water pollution control activities in the Public Health Service
of the Federal Security Agency and in the Federal Works Agency, and for
other purposes.
Be it enacted by the Senate and House of Representatives of the
United States of America in Congress assembled,
TITLE I—RESEARCH AND RELATED PROGRAMS
DECLARATION OF GOALS AND POLICY
SEC. 101. (a) The objective of this Act is to restore and maintain
the chemical, physical, and biological integrity of the Nation’s
waters. In order to achieve this objective it is hereby declared that,
consistent with the provisions of this Act—
http://www.epa.gov/region5/water/pdf/ecwa.pdf
Effects of Toxic Substances in Surface Waters
Most waste waters contain small amounts of chemical substances that with
inadequate dilution or treatment may significantly impair survival potential of
resident aquatic life. The capacity of rivers, lakes, and oceans to assimilate these
wastes and toxic materials is not infinite, and serious water quality degradation is
the inevitable result of the misuse and mismanagement of chemical resources.
The 20th century witnessed substantial growth of the chemical industry. Millions
of known chemical compounds exist, and an estimated 250,000 new compounds
are synthesized each year. Of this number, it is estimated that approximately
1,000 new chemicals find their way into the environment annually as the end
result of marketing, use, and disposal. The persistence and accumulation of
hazardous substances such as pesticides and recalcitrant organics have resulted in
the need for new and useful manufacturing containment and waste treatment
procedures that will help protect aquatic life.
http://www.fisheries.org/resource/page6.htm
But why not just measure
chemicals?
• Too many
– >1000 in the environment each year
– Analytical detection is very low – but often not low enough
• Too little testing
–
–
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Relatively little effects-testing of primary chemical
Even less of degradation products
Practically none on resident biota
Too many possible synergistic effects to test
• Chemicals in lotic systems are often transient.
Transient Presence
Ken Bencala USGS
So, what is a pollutant?
The introduction into the environment by
humans of a substance or energy (e.g., heat)
that will interfere with the natural processes or
legitimate uses of that environment
Forms of Pollutants (Hynes)
• Inert
– Sediments – e.g., from agriculture and forestry
• Poisons
– Pesticides, acids, industrial wastes (metals), gender benders
• Inorganic reducing agents
– Sulfides/sulfites – ↓ DO
• Oil
– Toxicity, barrier to air breathers
• Organic residues
– Sewage (human and animal) - ↓ DO, ↑ sedimentation
• Water temperature
– Changes normal regime
But it’s just not pollutants it’s
physical integrity as well
Deviation in natural flow regimes and
basin form and function
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•
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Water capture and diversion
Agriculture
Forestry
(Sub)urbanization
Mining
Advantages of Biological Measures
• Integration
– Temporal
• But …
– Stressor type
• But …
• Often the measure in which society is
most interested
– How many fish!
Advantages of Evaluating
Aquatic Invertebrates
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Ubiquitous
Extremely species rich
Sedentary (mostly)
Long life cycles (relatively)
Most often used
– All states, multiple federal programs in many nations
• Extremely long history
– Kolkwitz and Marsson (Saprobity)
• Cute
But – ongoing research is needed
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Integration?
Other habitats (particularly large rivers)
Cause and effect often speculative
More basic biology/ecology is necessary
Poor knowledge of natural distributions
Better taxonomy (particularly e.i.)
• …  should keep us in work for a long time!
Scales of Monitoring
(Biological levels)
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Biochemical/physiological
Individual
Population
Community (assemblage)
Ecosystem
Each level generally has an associated temporal scale associated with it
Biochemical/Physiological
• Enzyme activity
• Respiration
• Metal partitioning
– MBPs
• Crucial to our
understanding of
mode of action
Individual/Organism
• Deformities
– Chironomidae
– Gender-benders in
fishes
• Behavior
– Avoidance
• Life-history
– Hatching success
• Sentinel organisms
– Body burdens
Warwick: midge deformities
Populations and assemblages
• More often used
– Biotic indices
• The link that is often
missing
– High variance
• At least how we
currently measure
it/them
Community
Ecosystem
• Not often done
– Expensive
– Difficult to replicate
• But ELA
• Where we would like
to be because
– Evaluating processess
not just structure and
function
Hubbard Brook: Likens et al.
Experimental Lakes Area:
Schindler et al.
Mesocosms: principally lakes
but:
SNARL
Other methods
• Toxicity testing
– Acute and chronic
– Single species and multiple species
– Laboratory and field (Clements)
• Paleolimnological Methods
– Midge (and others) head capsules
• Sediment dating
• bioturbation
Community
Better term – assemblage
Why? – but we’ll use
Community
But also Why the “community” level?
• In most cases, save T&Es, there isn’t a single
species with which we’re concerned
– None identified as “diagnostic” of any given stressor
and
• We’re not talking salmon here
– High (possibly unmanageable variance)
• Rethink (i.e., test) different approaches
– Evan Hornig
• Ubiquitous – yes, but we expect species
turnover in space and time
• Used more often than any other level of
biological organization
Are these two approaches
different?
• Quantitative
– Most studies in the US
before 1989 (and some
after)?
– Collection “quantitative”
– Relative small spatial scale
– Replication
• But was it proper?
– High resolution taxonomy
• Qualitative
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Most studies post RBP
Collection “qualitative”
Much larger spatial scale
Considered un-replicated
• But probably replicated at
the right spatial scale
– Taxonomy likely less
resolved
• But …not always
What’s the question?
What’s the point?
• Describe a site (= sample unit) based on
the species (or types) present and the
distribution of individuals among these
species.
• Compare and contrast between/among
sites.
Types of measures
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Richness
“Enumerations”
Diversity
Similarity
Biotic indices
“Functional” (e.g., FFGs)
Combination = multimetrics
Multivariate
Richness (=S)
• The most frequently used “single” measure
– Often determined for a subset of the assemblage
• EPT
– Considered less tolerant of “pollution”
• And – at taxonomic levels other than species
• Assumption is that S ↓ with ↑ impairment – but …
– Variable in space and time
• Think of all the reasons we discussed
– Extremely method sensitive
• Field – not well tested
• Lab – some testing
• Rarefied
– We now know this but …
• No standard method
– Lab and/or computer
• What is it’s meaning (Courtemanch)
– An index of richness/evenness
Inflated richness as a function of
sorted N
“Enumerations”
• “Simplest” measure
– Total number of individuals – but …
• 0 – 100,000 m-2 (mean = 4000)
– Therefore subsampling is necessary
– ↑ error
– Total number of individuals within a group
• Taxonomic, FFG, etc.
• Often standardized to 100 = percentage composition
– % within a group
• Taxonomic (e.g., % EPT)
• FFG (e.g., % shredders
• Ratios (% EPT/ (% Chironomidae +% EPT)) but …
• Expected response is a function of the hypothesized response of the
group to the stressor
– High temporal variability
– Meaning ???
Diversity
• Was the summary measure of the ’60s and ’70s
– Hurlbert (1971) rightfully questioned it’s value
• Still a part of many “multimetrics”
• Many, many different formulae
– Shannon, Simpson, etc.
– “Integrates” richness and evenness because 2 sites may have similar
richness but extremely different distributions of individuals among the
species …e.g.,
• Species
•
•
A
90
40
B
5
30
C
3
20
D
1
6
E
1
4
• Assumption is that diversity ↓ as impairment ↑ but …
– Many factors influence the “diversity” of a site (= alpha diversity), such
as …
• The species available in the region (gamma diversity)
• Productivity, habitat diversity, and all the factors we talked about that
influence S
As an example: Shannon
n
H   pi log pi
i 1
where,
pi = the percentage of the ith species and there are n total species.
Note that the identify of the species is not required – only the
differentiation of one species from another.
Diversity is often viewed in light of evenness (J)
J  H / H max
,where
H max  log S
Highly correlated with S
Similarity Measures
(my personal favorites)
• Can be based on:
– Presence/absence data
– Percentage composition
– Abundance
• Objective:
– As defined, evaluate the similarity between (more so than
among) unimpaired vs. impaired sites.
• Assumption
– ↑ impairment ↓ similarity – but …
•
•
•
•
Nasty to work with
Difficult to summarize
Often are non-linear with increasing difference
But … again – seem more like what we “see” when we look at two
pans of bugs!
Jaccard Coefficient and
Percentage Similarity
JCbc 
abc
a b  c
where,
a = the number of species in common,
b = the number of species only in sample b
c = the number of species only in sample c
s
PS jk  1 
x
i 1
ij
 xik
s
 max( x , x
i 1
ij
ik
)
Present in
B and C
Only
present in
B
Present in
C and B
a
b
Only
present in
C
c
d
PSjk = percentage similarity between sample j and
sample k
xij = the abundance of species i in sample j
xik = the abundance of species i in sample k
s = the total number of species in samples j and k
Biotic Indices
• Numerous have been developed
– Saprobien Index (Kolkwitz and Marsson 1909)
• Valences
– In the US, the most often used measures are those developed by
Hilsenhoff
• Family Biotic Index
• Modified for season, taxonomic level, etc.
• Methods are dependent on the assignment of (in)tolerance values
• Assumptions
– ↑ impairment (normally organic) ↓ or ↑ biotic index depending on how it
is scaled
– Tolerance values are rarely empirically derived
• Often the derivation and application are circular
• Tolerances principally represent response to organic pollution
– Sensitive to taxonomic level
Weighted-average
n
  abundancei  tolerancei
i
n
 abundance
i
i
Measures of “function”
• Functional feeding group
– Should be based on method of food acquisition
• But often based on gut analysis
– Problem with what is or is not assimilated
• Distinction between
– FFG
• Scrapers, shredders, collector -gatherers and –filterers, predator … vs:
– Trophic level
• Detritivore, herbivore, omnivore, carnivore
• Mobility or lack thereof
– Clingers, sprawlers, swimmers, …
• Assumption
– Response is some function of the disturbance
– Most often based on % composition therefore sensitive to all those
factors that can influence % composition temporally and spatially
Combinations (= multimetrics)
• First developed by Jim Karr for fish
– Index of Biotic Integrity
• Based on the concept of economic indices
– Regardless, the idea is that no single measure will indicate the status of
a site therefore, it’s necessary to combine a number of different
measures (=metrics)
– Metrics are chosen that represent a range of response types (e.g.,
richness, % composition, diversity, ffg, biotic indices)
• They also are chosen to maximize differences between reference and
impaired.
– These individual measures are scaled and combined additively (most
often) and then often rescaled to range from 1 to 10
• Identifying impairment is based on a sites “value” relative to the established
range
• Well …
– If one measure is intractable – maybe adding up a bunch will make
sense???
– It’s really not that bad – sorry.
Go back to similarity slide
Multivariate Methods
Oh my!
Multivariate Methods
• Using all the data simultaneously
– Often both species and environmental
Multivariate
• Direct gradient analysis
– Variation is species distributions are are determined
• Often then related to environmental variables
• Inference
– Species distributions are used to infer environmental variables
• Temperature in Montana
• Indirect gradient analysis
– Searches for gradients in species data which are interpreted in
terms of environmental data
• Constrained ordination
– Axes of variation in species data is constrained within the
variation in environmental data.