Il valore aggiunto della limnologia comparata: un confronto tra laghi delle Terre Alte per lo studio dei cambiamenti climatici

CNR – Istituto per lo Studio degli EcosistemiVerbania

Andrea Lami Monica TolottiIASMA Research and InnovationCentre, Edmund Mach Foundation, S. Michele all’Adige

Convegno “L’acqua nelle Terre Alte: un percorso di ricerca attraverso il sistema alpino” – 04/12/2015, Verbania

4

Climate

Ecosystemsecologicalresponses?

Terrestrial ecosystems

“There is now ample evidence of the ecological impacts of recent climatechange, from polar terrestrial to tropical marine environments. The responsesof both flora and fauna span an array of ecosystems and organizationalhierarchies, from the species to the community levels. Despite continueduncertainty as to community and ecosystem trajectories under global change,

our review exposes a coherent pattern of ecological changeacross systems. Although we are only at an early stage in the projectedtrends of global warming, ecological responses to recent climate change arealready clearly visible.”

Fig. Regional coherence (expressed as correlation coefficients) between pairs of six alpine lakes in the Austrian ‘Salzkammergut’region shown as box‐whisker plots. Box limits are the 25th and 75th percentile; whiskers indicate the 10th and 90th percentile. Inthese boxes, the solid line is the median, the dashed line the mean. Physical = surface temperature, light attenuation and Secchi‐depth; chemical = pH, conductivity and oxygen concentration; nutrients = total phosphorus, total nitrogen and dissolved silica;biological = chlorophyll‐a and phytoplankton biomass. (Modified from Dokulil and Teubner, 2002)

Dokulil et al 2010. The impact of CC on Lakes in Central Europe

5

Climate

Lakes ecologicalresponses?

6

Climate

What are the components of ecosystems vulnerability?

Ecosystemvulnerability

Sensibility(Responsesamplitude)

Capacity of responses(Adaptations)

LowerIncrease

Physical responses

Degree of coherenceamong lakes(Dokulil et al., 2010; 

Livingstone et al., 2010)

Local humanpressure

Exposure

Does local human impact increase ecosystems vulnerability to climate change?

i.e. 

Local weather, topography

(Gallopin, 2006; Adger,2006; Mumby et al., 2014)

Aletsch Glacier

1979 1991 2002

?

2050

SIL‐Austria meeting 2014

Fig. 1. a) Lakes, rivers, glaciated areas and main sub‐basins area are reported, together with the reference weather station. b) Hypsometric curve and pond distribution.

Elevation ranges from 950 to 3905 m a.s.l. (Mean = 2425 m)

Ortles‐Cevedale mountain group (Stelvio National Park, southern Alps, Italy, ~600 km2)

Fig. 3. Changes that have occurred since 1954 in the pond population: 

a) Total surface area of ponds. The vertical bars represent the uncertainty associated with the measurement;

b) Total number of ponds;c) Mean elevation of the entire pond 

population.

+0.5%  ‐5.9% (1954‐07) 

>>>  In the recent fifty years, no significant changes in the size and number of ponds;

>>>  but, a substantial increasein the mean elevation of the entire pond population,   +55 (±3.5) m

EUCOP4, Évora, Portugal, June 18.‐21. 2014 

Permaqua sampling sites

Italy

Austria

HKKG

WI

UL

AR

MA SCH

HK  = Hochebenkar (Ötztal)KG  = Krumgampen (Kaunertal)WI  = WindachtalMA = MatschertalSCH = SchnalstalUL   = UltentalAR  = Ahrntal

Active RG in S‐TyrolRG‐impacted running waters and springsRG‐impacted lakes (with impacted/reference tributaries)Reference high mountain lakes (project Emerge, 2000)

Bozen/Bolzano

Innsbruck

Meran/Merano

EUCOP4, Évora, Portugal, June 18.‐21. 2014 EUCOP4, Évora, Portugal, June 18.‐21. 2014 

Permaqua – water chemistry

Impacted sites: lower pH, higher solute (Ca, Mg, SO4, Si) and metal concentrations.

*    = partial datan.a. = not available

Reference Impacted  Reference Impacted 

Nr. 11 20 7 13

EC S cm‐1 71 (12‐65) 185 (68‐395) 47 (14‐130) 188 (12‐609)pH 6.7 (5.9‐7.5 ) 6.2 (5.1‐7.6) 7.3 (6.5‐8.1) 6.1 (4.8 ‐7.7)Na mg L‐1 0.8 (0.3‐1.9) 1.4 (0.8‐2.2) 0.5 (0.3‐0.9) 1.3 (0.2‐2.1)K mg L‐1 0.6 (0.1‐1.9) 1.3 (0.1‐2.0) 0.4 (0.2‐0.6) 0.5 (0.2‐2.1)Ca mg L‐1 9.2 (1.7‐36.5) 22.8 (6.5‐38.0) 6.1 (1.6‐20.2) 16.8 (1.6‐42.5)Mg mg L‐1 2.1 (0.2‐7.6) 7.9 (2.4‐20.0) 1.1 (0.2‐3.7) 12.3 (0.1‐56.0)NH4 g L‐1 7 (2‐19) 4 (1‐8) 7 (2‐19) 10 (3‐30)Cl mg L‐1 0.2 (0.1‐0.8) 0.2 (0.1‐0.3) 0.1 (0.1‐0.2) 0.2 (0.10.6)NO3 g L‐1 148 (0‐653) 168 (1‐392) 189 (10‐394) 171 (30‐315)SO4 mg L‐1 24 (2‐110) 87 (28‐183) 7 (2‐16) 91 (2‐318)Al g L‐1 2 (0‐10) 235 (0‐1125) n.a. 0 (0‐2) *Ni g L‐1 1 (0‐4) 32 (0‐167) n.a. 0 *Mn g L‐1 2 (0‐16) 25 (0‐131) n.a. 0 *Co g L‐1 0 3 (0‐15) n.a. 0 (0‐1) *Zn g L‐1 2 (0‐8) 19 (0‐99) n.a. 0 *Sr g L‐1 2 (0‐9) 13 (0‐58) n.a. 0 *Si g L‐1 1030 (310‐3240) 2054 (540‐3950) 1043 (737‐1694) 1769 (740‐3050)

Running waters Lakes

EUCOP4, Évora, Portugal, June 18.‐21. 2014 EUCOP4, Évora, Portugal, June 18.‐21. 2014 

RGs in North Tyrol (A) – epilithic diatoms

-1.5

-1

-0.5

0

0.5

1

1.5

-1.5 -1 -0.5 0 0.5 1 1.5

NM

DS

dim

ensi

on 2

NMDS dimension 1

HK-R2

KG-1

HK-R1

KG-R3

KG-S

HK-1

KG-2

KG-3

KG-R1

KG-R2

HK-2

NMDS: Non-Metric Multidimensional Scaling on diatoms with relative abundance ≥0.5%(PCA based on Bray-Curtis dissimilarity matrix, suitable for dispersed biological data)

DIM 2:Psammothidium sacculum : 0.82***Psammothidium bristolicum: 0.80*Frustulia crassinervia : 0.72 *Brachysira brebissonii : 0.60*

DIM 1:Achnanthidium minutissimum: -0.82***Eunotia intermedia: -0-78**Encyonema minutum: -0.76**Diatoma mesodon: -0.75**Hannaea arcus: -0.75**

Eunotia exigua: 0.85**Pinnularia sinistra: 0.82**Psammothidium acidoclinatum: 0.77**Psammothidium helveticum: 0.73**Psammothidium marginulatum: 0.62*

* = p<0.05, ** = p<0.01, *** = p<0.001pH: ‐0.93***Zn:   0.75**Si:    0.70*

Al:  0.59*

Study area

High altitude lakes (above the local tree line) in the Western Alps (Ossola and Sesia valleys, Piedmont, Italy):

4 sites with continous chemical data(1‐4 samples per year) since the late 1970s

about 40 survey lakes with long‐termdiscontinuos data

• Area subject to high deposition of atmospheric pollutants, transported with the air masses from lowland areas (e.g. Plain of River Po)

• Climate change has proved to be more intense in mountain areas, with several effects on water bodies (water quantity and quality)

Among the lakes with the greatest SO4 increase, there are lakes with (active) rock glaciers in the catchment

0

50

100

150

1978 1986 1994 2002 2010

SO4= (µeq-1)

e.g. Boden lakes

Glaciers and permafrost

200

Maps by L. Paro, ARPA Piemonte

15 lakes located in the Ossola Valley were sampled in 2000 (early autumn). The same lake was visted also in 2 0 0 1 t o r e c o v e r t h e minithermistor data logger.

and 14 in Ticino

The lakes were chosen on the basis of the different lithological c o m p o s i t i o n s o f t h e i r catchments and consequently of their varying sensitivity to Sampling material

Survey lakes

Experimental site:

:: water chemistry, chl a, phytoplankton, zooplankton,

bacterial abundance, epilithic diatoms, sediments (diatoms, cladocera, total C, N and S, pigments). : skyline measurements, minithermistor,

sediment traps (2 lakes), thermistor chains (3 lakes),

Considered variables

Other activities

benthos,

data collation for GIS,

samples were collected and sent to the laboratories responsible for the analyses : soil (1 lake); chironomids, POPs, metal, SCPs in the sediment.

AWS and hydrological balance (2 lake).

Principali parametri chimici e fisici rilevati e analizzati per il progetto EMERGE

Lago Data di Profondità Azoto tot Fosforo tot pH Alcalinitàcampionamento (m) (g N l-1) (µg P l-1 ) medio media (eq l-1)

Panelatte 07/09/2000 5 450 5 7,11 113Paione Inf 12/09/2000 14 350 2 6,65 39

Paione Med 12/09/2000 5 440 5 6,53 34Paione Sup 13/09/2000 12 430 6 6,02 3Muino Inf 14/09/2000 2 180 7 6,42 32Matogno 21/09/2000 15 170 2 7,96 756

Variola Med 25/09/2000 4 330 4 6,21 17Variola Sup 25/09/2000 4 260 4 6,31 17Capezzone 26/09/2000 7 130 2 6,83 138Boden Inf 27/09/2000 7 240 2 7,98 523

Boden Sup 27/09/2000 6 370 4 7,81 415Grande 03/10/2000 6 250 1 5,73 0

Sfondato 03/10/2000 3 340 2 5,58 0Pojala 04/10/2000 16 110 6 7,19 251

Campo 05/10/2000 7 250 2 7,35 381

Water chemistry0.5

0.4

0.3

0.2

0.1

0.0

PT0

028

PT0

026

PT0

031

PT0

030

PT0

027

PT0

009

PT0

007

PT0

064

PT0

016

PT0

041

PT0

059

PT0

058

PT0

029

PT0

051

PT0

060

21 3

1. Lakes highly sensitive to acidification pH 5.6-6.2; alk 0-14 µeq l ; Ca 30-35 µeq l

2. Lakes moderately sensitive to acidificatin pH 6.2-6.6; alk 17-35 µeq l ; Ca 45-65 µeq l

3. Lakes with high buffer capacity pH 6.8-8.0; alk 110-760 µeq l ; Ca 120-780 µeq l

-1 -1++

-1

-1

-1

-1

++

++

Samples were taken at about 1 m depth.

The ionic content of the lakes varies between 100 and 1800 µeq l (conductivity in the range 7.5-80 µS cm at 20 °C). SO and NO concentrations are about 35-100 and 1-28 µeq l respectively.

For each sample the following variables were determined: pH, conducibility, alkalinity, major anions (SO , NO , Cl ) and cations (Ca , Mg , Na , K ), total nitrogen, total phosphorus, reactive silica.

A cluster analysis was performed on the chemical data and three groups of lakes were identi fied; the main facto r determining water chemistry of the groups is the dominant li thology of the catchments.

4 3

4

3

=

++ ++ + +

-1

=

-1

-1

-

-

- -

Dictyosphaerium sp. Pseudokephyrion sp. Chrysochromulina parvaFlagell. chryso. sp.1Colonial coccal cyano.Chromulina sp. 1Cfr. Codosiga botrytisFilamentous col. cyano.Achnanthes minutissimaRhodomonas cfr. minutaCryptomonas

sp.

Cyclotella comensis

Chromulina sp.

2

Synedra tenera

Flagell. chryso.

sp.2

Chlamydomonas

sp.

1M.

crassisquama

Oval crypto.

Flagell. chryso.

sp.3

Chryso sp.4

Mallomonas sp.

Dinobryon cylindricum

Chlamydomonas

sp.

2

Chromulina sp.

2

Scenedesmus

cfr.

linearisGymnodinium

sp.M.

komarkovae

0

A

B

Bray & Curtis index

0 10 20 30 40 50

Ind ml (Double square root)-1

PT0028PT0026

PT0031PT0030

PT0027PT0009

PT0007

PT0064

PT0016

PT0041PT0059

PT0058

PT0029

PT0051PT0060

Phytoplankton

Cluster Babundant specie:

, a speci es (s p.2) and an unident if ied chr ysophyte (chryso sp.4).

Dinobryon cylindricum Chromulina

Cluster Aphytoplankton populations abudant and characterised by the dominance of

sp., sp. and parva.Cryptomonas Dictyosphaerium

Chrysochromulina

very low species diversityand abundance.

Cluster 1 & 2form chemical

variables

Lakes as in based on chemistry

Cluster 3

The combined variance analysis of the lake clusters outlined by the multivariate analyses on phytoplankton and zooplankton data, respectively, allowed the identification of four principal lake types (three located on siliceous and one on carbonaceous bedrock), each one characterised by a certain combination of habitat features, which in turn influence trophic state, and phytoplankton and zooplankton species composition and functionality.

CCA ordination of 24 phytoplankton size classes CCA ordination of 14 zooplankton taxa

PT0009PT0059

PT0030PT0027PT0007

PT0041PT0058

PT0031PT0028

PT0029PT0051PT0060PT0026PT0064

PT0016

20 40 20 20 40 60 80 100 20 40 60 20 20 20

Plecop

tera

Trich

opter

aChir

onom

idae

Oligoc

haeta

Coleop

tera

Hydrac

arina

Turbe

llaria

Mollus

ca

Percentages

Benthos

PT0009PT0059

PT0030PT0027PT0007

PT0041PT0058

PT0031PT0028

PT0029PT0051PT0060PT0026PT0064

PT0016

20 40 10020 40 60 80 20 20 40 60

Tany

podin

aeOrth

oclad

iinae

Chiron

omini

Tany

tarsin

iPercentages

10020 40 60 80

Enchy

traeid

ae

10020 40 60 80 10020 40 60 80 20 40 60 80 100

Lumbri

culid

ae

Naidida

e

Tubif

icida

e

Percentages

PT0009PT0059

PT0030PT0027PT0007

PT0041PT0058

PT0031PT0028

PT0029PT0051PT0060PT0026PT0064

PT0016

Incr

easi

ng A

ltitu

de

Incr

easi

ng A

lkal

inity

Che cos’e la paleolimnologia?La paleolimnologia è la branca della limnologia che si occupa dello studio e dell’analisi dei sedimenti lacustri attraverso il prelievo di carote di sedimento.

ChironomidiChironomidiChironomidiChironomidi

Temperatura dellTemperatura dell’’acquaacquaFluttuazioni di livelloFluttuazioni di livelloCondizioni troficheCondizioni trofiche

Sostanza organicaSostanza organicaN, P, CaCON, P, CaCO33Silice Silice biogenicabiogenica

Utilizzo dei Utilizzo dei proxyproxy--recordrecord

Apporti clasticiApporti clasticiMetalliMetalli

Condizioni troficheCondizioni trofiche

BiodiversitBiodiversitààCondizioni troficheCondizioni trofiche

CladoceriCladoceriCladoceriCladoceri

Fluttuazioni dei ghiacciaiFluttuazioni dei ghiacciaiErosioneErosione

pHpHFosforoFosforoSalinitSalinitààProduzione primariaProduzione primaria

IntensitIntensitàà radiazione UVradiazione UVCondizioni di ossigenazioneCondizioni di ossigenazione

25 m 113 m 120m148 m59 m

PigmentiPigmentiPigmentiPigmenti

DiatomeeDiatomeeDiatomeeDiatomee

Carote Lago MaggioreCarote Lago Maggiore

Profonditàdell'acqua

Waterdepth

Questi sono alcuni dei parametri, in questo caso biologici e chimici, i cosiddetti proxy-record, tratti da diverse discipline, la cui minore o maggiore presenza nel sedimento indica particolari condizioni ambientali, fisiche, chimiche del lago e la loro evoluzione nel corso del tempo.

Proxy-record

0

4

8

12

16

20

24

28

32

36

40

44

48

52

56

60

64

68

72

76

80

84

Dep

th (c

m)

0.3 0.6

Sediment.

rate

1.3 1.6

Wet Density

50 100

H2O

10 20

Organic m

atter

0.8 1.0

430:410

150 300

CD

2 4

TC

0 300 600

b-Caro

ten

350 700

Echinenone

150 300

Zeaxa

nthin

150 300

Cantaxanthin

100 200

Myxoxan

thophil l

500 1000

Oscillaxa

nthin

30 60

Diadinoxanthin

200 400

Fucoxa

nthin

200 400

Diatoxanth

in

200 400

Alloxanthin

200 400

Lutein

15 30

Astaxa

nthin

7.0 8.5

TC-pH

15 30

TC-TP

0

4

8

12

16

20

24

28

32

36

40

44

48

52

56

60

64

68

72

76

80

84

Age

(ye

ars

D.C

.)

1935

1981

2011200519981988

19671971

1963

19001861

nmoli g LOI-1% fw % dwg cm-3g cm-2 y-1 g L-1mg gLOI-1

Geochemistry and pigments proxies

Secular ecological evolution of Lake Ledro (Trentino) as outlined by paleolimnological studies

0 2 4Number mg dry weight-1

1990

Years pH Spherical carbonaceous particles

1950

1900

1850

1800

1750

6.0

GlacierAdvance

GlacierAdvance

Aciddepositions

6.5 7.05.510Celsius degree

Air temperature

13

L. Paione Superiore, Val Bognanco

Paneveggio‐Pale di San Martino Natural Park

Latitude 46°17’1’’NLongitude 11°45’56’’EAltitude 1914 m a.s.l.Watershed area 0.36 km2

Surface 0.013 km2

Volume 49x106 m3

Depth (max) 8 mDepth (mean) 3.8 mSurrounding soil podsol or rankersBedrock quartziferous porphyry and sand‐stone

(Trevisan et al. 2014. J. limnol. 73) 

• The most significant variables resulted air temperature, hydrologic water level and pH.• Colbricon Inferiore doubled the amount of phytoplankton density and biomass

0

5

10

15

20

25

30

35

40

45

50

55

60

65

70

75

80 0 5 10 15

DWAgeAD

Dep

th ( c

m)

20 40

LOI

0 20 40 60

CD

0 1

TC

0 50 100 150

bb_C

ar

0 50 100 150

Lute

0 20

Discos

tella

stellig

eroide

s

0 20 40 60

Stauros

iraps

eudo

costr

uens

1550

1600

1650

1700

1750

1800

1850

1900

1950

2000

0

500

1000

1500

2000

2500

3000

3500

4000

4500

5000

5500

6000

6500

7000

7500

8000

8500

9000

9500

10000

10500

11000

11500

12000

12500

Age

(cal

yr B

P)

0 20 40 60 80

Tabu

laria

fascic

ulata

0 20 40

Stauro

sira c

ostru

ens

0 20 40 60

Stauro

sira m

icros

triata

0 20

Cyclot

ella k

rammeri

0 20 40 60 80

Discos

tella

stellig

eroide

s

0 20 40

Puncti

culat

a rad

iosa

0 20

Stauro

sira b

inodis

0 20

Stauros

ira br

evist

riata

0 20 40

Stauros

ira m

utabil

is

0 20 40

Stauros

ira ps

eudo

costr

uens

0 20 40 60

Pseud

ostau

rosira

ellip

tica

0

Aulaco

seira

alpig

ena

0

Dentic

ula te

nuis

0 20

Sellap

hora

laevis

sima

0 20

Sellap

hora

pupu

la

0

Amphora

lybic

a

Staurosira spp

0

500

1000

1500

2000

2500

3000

3500

4000

4500

5000

5500

6000

6500

7000

7500

8000

8500

9000

9500

10000

10500

11000

11500

12000

12500

Age

(cm

)

0 20 40 60

Alfa_c

ar

0 20 40 60

bb_C

ar

0 100 200

Fuco

x

0 20 40

Diadi

0 10 20

Diato

0 20 40 60

Allo

0 50 100

Lute

0 20 40

Echi

0 20 40

Myxox

0.0 1.0 2.0

Grazing

Himalaya, Khumbu-Himal region, Nepal, 31 lakes

Central Alps, Italy35 lakesSerra da

Estrela, Portugal, 9

lakes

SvalbardIslands, 3 lakes

CNR ISE remote lake dataset

ALP AND ANT HIM POR SVA0.0

0.1

0.2

0.3

0.4

0.5

N-NO3 (mg N L-1)Northern Patagonia18 lakes

Antarctica, Terra Nova Bay, 29 lakes

Sappiamo molto, ma NON ABBASTANZA!!!Necessità di acquisire informazioni di elevata qualità (metodi confrontabili, meta-dati)Necessità di un approccio interdisciplinare… affrontare le tematiche a livello di EcosistemaNecessità di una integrazione fra Osservazione delle Terra (remote sensing) e in-situ data

1. Estendere il database disponibile

2. Confrontare la risposte della comunità biologiche al cambiamento climatico e l’interazione con altri fattori

3. Valutare la sincronicità della risposta fra ambienti localizzati in aree geografiche differenti

4. Discriminare il « peso » dei fattori locali rispetto a quelli globali nell’influenzare la risposta delle comunità biologiche.

Riassumendo

Grazie per l’attenzione