Ormerod Feb 2009 - Birkbeck, University of London · The state of river ecosystems: a degraded past, an uncertain future? Steve Ormerod. 1. A crash-course in river ecology 2. River

The state of river ecosystems: a The state of river ecosystems: a degraded past, an uncertain future?degraded past, an uncertain future?

Steve OrmerodSteve Ormerod

1. A crash-course in river ecology

2. River modifications by people

3. Conservation challenges

4.Two linked examples of impairment• The effects of climate change• Recovery from acid rain

Conclusions

(Introduce themes for later speakers)

Rivers are dynamic and variable in spaceand time:

PhysicallyChemicallyEnergetically

… at a range of scales

Hubbard Brook Experimental Forest, New Hampshire

Stevens et al. 1995 FORESTRY 68 (2): 115-131 1995

The effects of clear-felling on N export from two Welsh catchments

Stoneflies

Caddis

Mayflies

Lateral dispersal in the adult stages of insects around Llyn Brianne streams

(Petersen et al. 2004 from Malaise trapping)

Tagliamento (Italy; Ramsar)

The river continuum concept

Vannote et al. 1980

Over 80 insect species incircumneutral streams at Llyn Brianne

Filter-feeding Philopotamus

Predatory Perla

Scraper-grazer Baetis

Importance to conservation:

• Recognised threats and rates of extinction• Physically complex: disproportionately large

species richness per unit volume • Globally significant functions (solute and energy

transport, migratory fishes…)• Extensive habitat network (e.g. > 24,000 km in

Wales alone; headwaters 80% of UK river length)

• Ecotonal nature: interaction with riparian zone (birds, mammals…)

• Increasingly emphasised in leglislation (e.g. Directives 92/43/EEC and 2000/60/EC)

Afon Irfon (River Wye/Afon Gwy SAC)

Afon Tywi SAC

NASA Earth Observatory

“Al Gore: An inconvenient truth”

Worlwide Fund for Nature

Rivers are likely to be highly climate-sensitive:• Ecological dependence on hydrology, hydraulics,

connectivity, floods/droughts• Small thermal mass strong link to air

temperature• Characterised by ectothermic organisms• Interactions between temperature, oxygen,

metabolic activity, growth, development, production, decomposition…

• Likely interactions between climate and other pressures: land-use, flood defence, abstraction, nutrients, acid rain

• Stream ecosystems track large-scale climatic phenomena (e.g. NAO)

J.M. Elliott 2000

Example 1:

A 25-year study of streams around Llyn Brianne

The Llyn Brianneexperiments….

…. established in 1981 to assess the role of land use in acidification – but also to test predicitons about recovery using replicatedreplicatedcatchment experiments.

LI1

LI2LI3

LI4LI5

LI6LI7LI8

CI1CI2

CI3

CI4CI5CI6

Llyn Brianne sitesLlyn Briannecatchments



Catchments treated by CaCO3 addition 1987/88

LI1

LI2LI3

LI4LI5

LI6LI7LI8

CI1CI2

CI3

CI4CI5CI6




Unmanipulated referencecatchments

LI1

LI2LI3

LI4LI5

LI6LI7LI8

CI1CI2

CI3

CI4CI5CI6


Circumneutral streams: richest in species

We asked:

1. Has there been any change in stream temperature or discharge ?

2. Has there been any response in invertebrate composition or abundance?

J. W. Hurrell et al. 2004

Hurrell’s NAO index.

Warm, wet, stormy

Cold, dry, calm



Warm, wet, stormy

Cold, dry, calm

Positive amplification



Warm, wet, stormy

Cold, dry, calm

Llyn Brianneproject starts

y = 0.2798x + 2.3696R2 = 0.3503

00.5

11.5

22.5

33.5

44.5

5

-6 -4 -2 0 2 4 6

NAO winter index

Mea

n te

mpe

ratu

re (D

ec-F

eb)

Stream temperature at Llyn Brianne (LI1) and the NAO

-5-4-3-2-10123456

1981

1983

1985

1987

1989

1991

1993

1995

1997

1999

2001

2003

Year

Durance & Ormerod Global Change Biology

NAO

°C

Trends in winter stream temperature at Llyn Brianne before and afteraccounting for NAO effects

0

1

2

3

4

5

1981 1986 1991 1996 2001

Win

ter t

empe

ratu

re in

°C

(b)

-2

-1

0

1

2

1981 1986 1991 1996 2001

Res

idua

ls o

f W

inte

r tem

pera

ture

(c)

+1.7 °C *** (1981-2005)


+1.4 °C*** in forest streams

Recent near-surface temperatures (Global average)

Similar increase in stream temperature in Scotland, Exmoor, S. England, upper Rhone, Switzerland, Austria…

0.200

0.400

0.600

0.800

1.000

1.200

1.400

1.600

1.800

1981

1983

1985

1987

1989

1991

1993

1995

1997

1999

2001

2003

1990-2020

Year-to-year trends in winter discharge on Plynlimon (winter, Q10)

m3 s-1

Effects on invertebrate composition and abundance

Trends in the abundance of stream invertebrates at Llyn Brianne withtemperature and through time

Abundances decline on average by 21% of the mean for every 1C rise


Coleopteran larvaeLarge LimnophilidaeBrachyptera risiWormaldia sp.Hydraena gracilisDiplectrona felixLeuctra fuscaPerlodes microcephalaCaenis sp.Helodes marginataHydropsyche instabilisTabanidaeBaetis niger

Cordulegaster boltoniiParaleptophlebia submarginataPisidium sp.HydracarinaSericostoma personatumAncylus fluviatilisHelichus substriatusOreodytes sanmarkiiPhilopotamus montanusNemurella picteti

CeratopogonidaeRhyacophila mundaAgabus spp.HydrophilidaeDrusus annulatusOulimnius tuberculatusLimnius volckmariChaetopteryx villosaPlectrocnemia conspersaSiphlonurus lacustrisGlossossoma conformis Dytiscidae larvae

Velia capraiHydropsyche siltalaiElmis aeneaHelodida spNemoura spp.TipulidaeProtonemura spp.Ecdyonurus spp.ChironomidaeLymnaeidaeLeuctra inermisLeuctra nigraIsoperla grammaticaHeptagenia lateralisOdontocerum albicorneHelophorus spp.OligochaetaChloroperla tripunctata

Dryops sp.Paraleptophlebia cinctaCrenobia alpinaLepidostoma hirtumGyrinus substriatusBaetis muticusEsolus parallelepipedusRhyacophila dorsalisLimnebius truncatellusSimuliidaeAmphinemura sulcicollisChloroperla torrentiumSilo pallipesAgapetus fuscipesPlectrocnemia geniculataBaetis rhodaniLeuctra hippopusRhithrogena semicolorataDiura bicaudata

DixidaePerla bipunctataHelodes minutaBaetis scambusAmphinemura standfussiAnacaena globulusMetalype fragilisAsellus sp.Phagocata vittaPsychomyia pusillaLeuctra moselyiLeptophlebia sp. (marginata)

-1 -0.5

0 0.5

1 1.5

2 2.5

3 3.5

4 4.5

DCA axis 3

Coleopteran larvaeLarge LimnophilidaeBrachyptera risiWormaldia sp.Hydraena gracilisDiplectrona felixLeuctra fuscaPerlodes microcephalaCaenis sp.Helodes marginataHydropsyche instabilisTabanidaeBaetis niger



CeratopogonidaeRhyacophila mundaAgabus spp.HydrophilidaeDrusus annulatusOulimnius tuberculatusLimnius volckmariChaetopteryx villosaPlectrocnemia conspersaSiphlonurus lacustrisGlossossoma conformis

CeratopogonidaeRhyacophila mundaAgabus spp.HydrophilidaeDrusus annulatusOulimnius tuberculatusLimnius volckmariChaetopteryx villosaPlectrocnemia conspersaSiphlonurus lacustrisGlossossoma conformis Dytiscidae larvae

Velia capraiHydropsyche siltalaiElmis aeneaHelodida spNemoura spp.TipulidaeProtonemura spp.Ecdyonurus spp.ChironomidaeLymnaeidaeLeuctra inermisLeuctra nigraIsoperla grammaticaHeptagenia lateralisOdontocerum albicorneHelophorus spp.OligochaetaChloroperla tripunctata

Dytiscidae larvaeVelia capraiHydropsyche siltalaiElmis aeneaHelodida spNemoura spp.TipulidaeProtonemura spp.Ecdyonurus spp.ChironomidaeLymnaeidaeLeuctra inermisLeuctra nigraIsoperla grammaticaHeptagenia lateralisOdontocerum albicorneHelophorus spp.OligochaetaChloroperla tripunctata





-1 -0.5

0 0.5

1 1.5

2 2.5

3 3.5

4 4.5

DCA axis 3

-1 -0.5

0 0.5

1 1.5

2 2.5

3 3.5

4 4.5

-1 -0.5

0 0.5

1 1.5

2 2.5

3 3.5

4 4.5

DCA axis 3

Increase in temperature

The optimum and amplitude of each invertebrate species in circumeutralstreams at Llyn Brianne on ordination axes related to temperature


Climate change projections for Wales

7 – 156 – 10Change in winter discharge (% )

0.8 – 2.20.5 – 1.4Change in winter temperature (°C)

2050s2020s

Projected future climatic effects on upland stream invertebrates at LlynBrianne according to CLIO

25% of typical mean richness; 12% of the total species pool

Consequences for productionand energy transfer?


Interactions with recovery from acid rain

Mean annual dissolved aluminium (<0.45 m) in Welsh streams in relation to catchment afforestation, and invertebrate species richness

(Ormerod et al. 1987)

Acid forest streams

3**00.61**Diplectrona felix

No gains

3**00.39Wormaldia sp3**00.47*Baetis muticus

Limed streams:

6**00.68***Wormaldia sp.200.48*Ephemerella ignita

Acid moorland streams:

Frequency of occurrence (%)(1995-2005)

Frequency of occurrence (%)(1985-1995)

Trends in abundance

Significant time-trends among acid-sensitive species at Llyn Brianne

(Durance & Ormerod unpubl)

4.04.55.05.56.06.57.07.58.08.5

pH

Kowalik & Ormerod in press Global Change Biology

Episodes of low pH are still widespread across Wales despite recovery in mean conditions (2002/2003 data).

Base-flow pH

Storm-flow pH

r2 = 0.82

3.5

4

4.5

5

5.5

1980 1985 1990 1995 2000 2005

Year

Min

imum

pH

a) CI1

r2 = 0.64

3.5

4

4.5

5

5.5

1980 1985 1990 1995 2000 2005

Year

Min

imum

pH

b) CI4

r2 = 0.78

3.5

4

4.5

5

5.5

1980 1985 1990 1995 2000 2005

Year

Min

imum

pH

c) LI1

r2 = 0.59

3.5

4

4.5

5

5.5

1980 1985 1990 1995 2000 2005Year

Min

imum

pH

d) LI8

ForestMoorland

pH minima in unmanipulated sites at Llyn Brianne

(Durance & Ormerod in press)

Summer discharge

Winter discharge

0.073.65 (1,19)-1.1 (2.04; 13)1.8 (4.80; 8)CI4

NS1.26 (1,21)-1.5 (5.8; 13)2.0 (9.2; 10)LI1

NS0.01 (1,23)-0.05 (2.9; 13)0.06 (3.4; 12)LI8

0.044.73 (1,19)1.6 (4.4; 10)-1.5 (1.8; 11)CI4

0.083.31 (1,21)2.6 (7.7; 12)-2.8 (6.5; 11)LI1

0.0059.59 (1,23)1.6 (2.5; 13)-1.7 (2.8; 12)LI8

PF (df)Wet years (SD; n)Dry years (SD; n)Site

Climatic effects on residual H+ in unmanipulatedmoorland and forest streams, 1981-2005

Wet winters elim

inate 20-40% of the

25-year decrease in H+

Example 2:River Wye salmonids.

EA data (Clews & Ormerod unpubl.)

Rel

ativ

e D

ensi

ty

0.5

1.0

Trou

t juv

enile

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1997

1998

1999

2000

2002

2003

2004

Year

-1.0

-0.5

0.0

0.5

1.0

1.5

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1997

1998

1999

2000

2002

2003

2004

Year

Salm

on ju

veni

le

-1.0

-0.5

0.0

0.519

85

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1997

1998

1999

2000

2002

2003

2004

Year

Trou

t fry

0.0

0.5

1.0

Trou

t juv

enile

N= 90 91 53 51 57 59 59 69 148 44 57 123 82 102 17 39 139 35

N= 92 93 55 53 58 60 61 72 151 47 59 126 82 105 17 39 145 35

Rel

ativ

e D

ensi

ty

0.5

1.0

Trou

t juv

enile

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1997

1998

1999

2000

2002

2003

2004

Year

-1.0

-0.5

0.0

0.5

1.0

1.5

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1997

1998

1999

2000

2002

2003

2004

Year

Salm

on ju

veni

le

-1.0

-0.5

0.0

0.519

85

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1997

1998

1999

2000

2002

2003

2004

Year

Trou

t fry

0.0

0.5

1.0

Trou

t juv

enile

N= 90 91 53 51 57 59 59 69 148 44 57 123 82 102 17 39 139 35

N= 92 93 55 53 58 60 61 72 151 47 59 126 82 105 17 39 145 35

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1997

1998

1999

2000

2002

2003

2004

Year

-1.0

-0.5

0.0

0.5

1.0

1.5

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1997

1998

1999

2000

2002

2003

2004

Year

Salm

on ju

veni

le

-1.0

-0.5

0.0

0.519

85

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1997

1998

1999

2000

2002

2003

2004

Year

Trou

t fry

0.0

0.5

1.0

Trou

t juv

enile

N= 90 91 53 51 57 59 59 69 148 44 57 123 82 102 17 39 139 35

N= 92 93 55 53 58 60 61 72 151 47 59 126 82 105 17 39 145 35

Rel

ativ

e D

ensi

ty

-1.0

-0.5

0.0

0.5

1.0

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1997

1998

1999

2000

2002

2003

2004

Year

Trou

t juv

enile

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1997

1998

1999

2000

2002

2003

2004

Year

-1.0

-0.5

0.0

0.5

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1997

1998

1999

2000

2002

2003

2004

Year

Trou

t fry

-1.0

-0.5

0.0

0.5

1.019

85

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1997

1998

1999

2000

2002

2003

2004

Year

Trou

t juv

enile

N= 90 91 53 51 57 59 59 69 148 44 57 123 82 102 17 39 139 35

N= 92 93 55 53 58 60 61 72 151 47 59 126 82 105 17 39 145 35

N= 92 93 55 53 58 60 61 72 151 47 59 126 82 105 17 39 145 35

Rel

ativ

e D

ensi

ty

-1.0

-0.5

0.0

0.5

1.0

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1997

1998

1999

2000

2002

2003

2004

Year

Trou

t juv

enile

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1997

1998

1999

2000

2002

2003

2004

Year

-1.0

-0.5

0.0

0.5

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1997

1998

1999

2000

2002

2003

2004

Year

Trou

t fry

-1.0

-0.5

0.0

0.5

1.019

85

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1997

1998

1999

2000

2002

2003

2004

Year

Trou

t juv

enile

N= 90 91 53 51 57 59 59 69 148 44 57 123 82 102 17 39 139 35

N= 92 93 55 53 58 60 61 72 151 47 59 126 82 105 17 39 145 35

N= 92 93 55 53 58 60 61 72 151 47 59 126 82 105 17 39 145 35

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1997

1998

1999

2000

2002

2003

2004

Year

-1.0

-0.5

0.0

0.5

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1997

1998

1999

2000

2002

2003

2004

Year

Trou

t fry

-1.0

-0.5

0.0

0.5

1.019

85

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1997

1998

1999

2000

2002

2003

2004

Year

Trou

t juv

enile

N= 90 91 53 51 57 59 59 69 148 44 57 123 82 102 17 39 139 35

N= 92 93 55 53 58 60 61 72 151 47 59 126 82 105 17 39 145 35

N= 92 93 55 53 58 60 61 72 151 47 59 126 82 105 17 39 145 35

Rel

ativ

e D

ensi

ty

0.5

1.0

Trou

t juv

enile

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1997

1998

1999

2000

2002

2003

2004

Year

-1.0

-0.5

0.0

0.5

1.0

1.5

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1997

1998

1999

2000

2002

2003

2004

Year

Salm

on ju

veni

le

-1.0

-0.5

0.0

0.519

85

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1997

1998

1999

2000

2002

2003

2004

Year

Trou

t fry

0.0

0.5

1.0

Trou

t juv

enile

N= 90 91 53 51 57 59 59 69 148 44 57 123 82 102 17 39 139 35

N= 92 93 55 53 58 60 61 72 151 47 59 126 82 105 17 39 145 35

Rel

ativ

e D

ensi

ty

0.5

1.0

Trou

t juv

enile

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1997

1998

1999

2000

2002

2003

2004

Year

-1.0

-0.5

0.0

0.5

1.0

1.5

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1997

1998

1999

2000

2002

2003

2004

Year

Salm

on ju

veni

le

-1.0

-0.5

0.0

0.519

85

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1997

1998

1999

2000

2002

2003

2004

Year

Trou

t fry

0.0

0.5

1.0

Trou

t juv

enile

N= 90 91 53 51 57 59 59 69 148 44 57 123 82 102 17 39 139 35

N= 92 93 55 53 58 60 61 72 151 47 59 126 82 105 17 39 145 35

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1997

1998

1999

2000

2002

2003

2004

Year

-1.0

-0.5

0.0

0.5

1.0

1.5

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1997

1998

1999

2000

2002

2003

2004

Year

Salm

on ju

veni

le

-1.0

-0.5

0.0

0.519

85

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1997

1998

1999

2000

2002

2003

2004

Year

Trou

t fry

0.0

0.5

1.0

Trou

t juv

enile

N= 90 91 53 51 57 59 59 69 148 44 57 123 82 102 17 39 139 35

N= 92 93 55 53 58 60 61 72 151 47 59 126 82 105 17 39 145 35

Rel

ativ

e D

ensi

ty

-1.0

-0.5

0.0

0.5

1.0

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1997

1998

1999

2000

2002

2003

2004

Year

Trou

t juv

enile

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1997

1998

1999

2000

2002

2003

2004

Year

-1.0

-0.5

0.0

0.5

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1997

1998

1999

2000

2002

2003

2004

Year

Trou

t fry

-1.0

-0.5

0.0

0.5

1.019

85

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1997

1998

1999

2000

2002

2003

2004

Year

Trou

t juv

enile

N= 90 91 53 51 57 59 59 69 148 44 57 123 82 102 17 39 139 35

N= 92 93 55 53 58 60 61 72 151 47 59 126 82 105 17 39 145 35

N= 92 93 55 53 58 60 61 72 151 47 59 126 82 105 17 39 145 35

Rel

ativ

e D

ensi

ty

-1.0

-0.5

0.0

0.5

1.0

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1997

1998

1999

2000

2002

2003

2004

Year

Trou

t juv

enile

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1997

1998

1999

2000

2002

2003

2004

Year

-1.0

-0.5

0.0

0.5

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1997

1998

1999

2000

2002

2003

2004

Year

Trou

t fry

-1.0

-0.5

0.0

0.5

1.019

85

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1997

1998

1999

2000

2002

2003

2004

Year

Trou

t juv

enile

N= 90 91 53 51 57 59 59 69 148 44 57 123 82 102 17 39 139 35

N= 92 93 55 53 58 60 61 72 151 47 59 126 82 105 17 39 145 35

N= 92 93 55 53 58 60 61 72 151 47 59 126 82 105 17 39 145 35

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1997

1998

1999

2000

2002

2003

2004

Year

-1.0

-0.5

0.0

0.5

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1997

1998

1999

2000

2002

2003

2004

Year

Trou

t fry

-1.0

-0.5

0.0

0.5

1.019

85

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1997

1998

1999

2000

2002

2003

2004

Year

Trou

t juv

enile

N= 90 91 53 51 57 59 59 69 148 44 57 123 82 102 17 39 139 35

N= 92 93 55 53 58 60 61 72 151 47 59 126 82 105 17 39 145 35

N= 92 93 55 53 58 60 61 72 151 47 59 126 82 105 17 39 145 35

Trends in standardised density of 0+ salmonids, Wye catchment


b) Summer temperature

12

14

16

18

20

1980 1985 1990 1995 2000 2005Year

°C

c) Winter temperature

456789

1980 1985 1990 1995 2000 2005Year

°C

d) Winter temperature residual after NAO

-2

-1

0

1

2

1980 1985 1990 1995 2000 2005Year

Res

idua

l tem

pera

ture

a) Annual temperature

89

1011121314

1980 1985 1990 1995 2000 2005year

°C

(Clews & Ormerod unpubl.)

Reconstructed temperature trends in small (○) and larger (●) tributaries, Wye catchment

0

5

10

15

-2 -1 0 1 2

PC1 summer 'climate' last year

Juve

nile

sal

mon

den

sity

/ 10

0m2

0

5

10

15

-2 -1 0 1 2

PC1 summer 'climate' last year

Juve

nile

trou

t den

sity

/ 10

0m2


0+ salmonids in the Wye decline most in hot, dry summers

Example 3:

Have there been any climaticeffects on southern chalk-streams?

Llyn Brianne winter

0

2

4

6

8

10

12

1975 1980 1985 1990 1995 2000 2005 2010

Years

°C

Residuals after NAO effects

-1.5

-1

-0.5

0

0.5

1

1.5

1975 1980 1985 1990 1995 2000 2005 2010

Years

Res

idua

ls f

rom

NAO

Itchen winter

0

2

4

6

8

10

12

1975 1980 1985 1990 1995 2000 2005 2010

Years

°C

Residuals after NAO effects

-4

-3

-2

-1

0

1

2

3

1975 1980 1985 1990 1995 2000 2005 2010

Years

Res

idua

ls f

rom

NAO

Corresponding temperature trends in lowland Itchen and upland Welsh streams(mean winter values).

Real (Itchen) and modelled (Bere, Avon) increases in average winter and summer temperature (with SE) between 1980 and 2006 in three rivers in southern Britain. Values in parentheses are temperature increases over the period covered by invertebrate data (1989-2006).

Stream Winter temperature °C Summer temperature °C

Itchen 2.7 ± 0.7 (1.9 ) 1.3 ± 0.8 (0.9)

Avon 2.4 ± 1.3 (1.7) 1.2 ± 1.4 (0.8)

Bere 1.8 ± 0.9 (1.2) 0.9 ± 1.1 (0.6)

Durance & Ormerod (in press using EA data)

Effects on phenology rather than distribution?

Group 1

0.8

1

1.2

1.4

1.6

1.8

2

2.2

1988 1993 1998 2003

Years

Aver

age

DC

A1

scor

es

Year

DC

A1

(a)

Highly significant changes in invertebrate assemblages in southern chalk-streams since 1990.

Durance & Ormerod (in press, using EA data)

Reflects gain in families typical of faster-flowing, well-oxygenated conditions

Year

mg/

l

2007

2006

2005

2004

2003

2002

2001

2000

1999

1998

1997

1996

1995

1994

1993

1992

1991

1990

2.6

2.4

2.2

2.0

1.8

1.6

1.4

1.2

1.0

BOD Group 1

Biochemical oxygen demand in chalk streams, 1990-2007

Currently investigatingeffects of varying dischargeon macrophytes andinvertebrates

Conclusions:• River ecosystems are ecologically diverse, but have been

affected historically by a range of human activities• Climate-change represents future uncertainty• Real evidence of climate-change effects on rivers (energy

transfer, species composition, salmonids…)• …but also evidence about positive management options:

i) reducing other pressures (water quality, abstraction…)ii) riparian-zone protection and enhancement

• Still major knowledge gaps (e.g. mechanisms; ecosystem function; resistance/resilience; interactions among stressors…)

• Other speakers in this series will explore these themes further: climate, conservation, management..

Ormerod Feb 2009 - Birkbeck, University of London · The state of river ecosystems: a degraded past, an uncertain future? Steve Ormerod. 1. A crash-course in river ecology 2. River

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