swaay butterfly monitoring analysis

46
Butterfly Monitoring: analysis and scientific use of data Chris van Swaay, De Vlinderstichting / Dutch Butterfly Conservation Butterfly Conservation Europe (BCE) Statistics Netherlands (CBS) Thousands of volunteers Adapted by Martin Wiemers (UFZ, BCE)

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Page 1: Swaay butterfly monitoring analysis

Butterfly Monitoring: analysis and scientific use of data

Chris van Swaay, De Vlinderstichting / Dutch Butterfly Conservation

Butterfly Conservation Europe (BCE)

Statistics Netherlands (CBS) Thousands of volunteers

Adapted by Martin Wiemers (UFZ, BCE)

Page 2: Swaay butterfly monitoring analysis

What is butterfly monitoring?

“Collect information on the changes in butterfly abundance” We have to follow a protocol to detect real trends Fieldwork • Basis: samples • Regular counts • Fixed method In the Netherlands 400 transects generate 200000

records per year

Page 3: Swaay butterfly monitoring analysis

Products

10

100

1000

1992 1994 1996 1998 2000 2002 2004

Woodland generalistsWoodland specialists

Species trends

Indicators

10

100

1000

1992 1994 1996 1998 2000 2002 2004 2006 2008

GeelsprietdikkopjeThymelicus sylvestris

Page 4: Swaay butterfly monitoring analysis

Criteria for indicators

• Scientific sound method • Sensitive • Affordable monitoring, available and routinely collected

data • Spatial and temporal coverage of data • Measure progress towards target • Policy relevance • Broad acceptance

Page 5: Swaay butterfly monitoring analysis

The start

• Ernie Pollard started the first BMS in the UK in 1976

Page 6: Swaay butterfly monitoring analysis

• 1976: start of the first Butterfly Monitoring Scheme in the UK

• Well founded by many scientific papers • Now at least 2500 transects in 14 countries • Every year our European volunteers

count once around the world (40.000 km)!

Butterfly Monitoring available and routinely collected

Page 7: Swaay butterfly monitoring analysis

Butterfly Monitoring Spatial coverage • New countries join in

every year • Most of them done

every year

Page 8: Swaay butterfly monitoring analysis

Butterfly Monitoring Temporal coverage

0

2

4

6

8

10

12

14

16

18

20

1975 1980 1985 1990 1995 2000 2005 2010

Num

ber o

f BM

S

Page 9: Swaay butterfly monitoring analysis

From transects to European indicator

• Location of the transects • Quality of the observer • Quality of the observations • Validation of the observations • Calculating trends • Building indicators

Page 10: Swaay butterfly monitoring analysis

From transects to European indicator

• Location of the transects • Quality of the observer • Quality of the observations • Validation of the observations • Calculating trends • Building indicators

Page 11: Swaay butterfly monitoring analysis

Choice of locations

• Free choice of transects (e.g. in the UK, Netherlands, Germany) – Pro: appealing to volunteers, easy to keep them motivated, rare

species included – Con: data is biased (but can be corrected by weighting)

• (Partly) random (e.g. France) – Pro: less bias – Con: sometimes transects on unattractive sites, no trends of rare

species (often the ones with high conservation value)

• Regular grid (e.g. Switzerland) – Pro: almost no bias – Con: hard to achieve (only on professional basis); no trends of

rare species (often the ones with high conservation value)

Page 12: Swaay butterfly monitoring analysis
Page 13: Swaay butterfly monitoring analysis
Page 14: Swaay butterfly monitoring analysis

From transects to European indicator

• Location of the transects • Quality of the observer • Quality of the observations • Validation of the observations • Calculating trends • Building indicators

Page 15: Swaay butterfly monitoring analysis

Basic idea

• We realise we can’t count all butterflies • But by taking samples we can estimate trends • As a consequence we don’t know the population size • But we can calculate changes in the population size

efficiently • With random or grid sampling transects are properly

distributed over the country • But in many countries recorders have a free choice • Solution: weighting

Page 16: Swaay butterfly monitoring analysis

Why weighting?

• Not all species are equally distributed over the country • Not all transects are equally distributed over the country.

In the Netherlands especially the dunes are ‘oversampled’, agricultural areas in the clay and peat regions are ‘undersampled’.

Page 17: Swaay butterfly monitoring analysis

Weighting by Dutch physical geographic region and main habitat type

Habitat types: • Woodland • Heathland • Agriculture • Open dunes • Urban • Moorland

Page 18: Swaay butterfly monitoring analysis

Distribution of the population over the strata

The distribution of each species per stratum is calculated. For example: Hipparchia semele

Dunes - mainland

Dunes - WaddenseaHeathland - north

Heathland - centre

Heathland - south

Page 19: Swaay butterfly monitoring analysis

Distribution of the transects over the strata

Dunes - mainland

Dunes - WaddenseaHeathland - north

Heathland - centre

Heathland - southdistribution

Page 20: Swaay butterfly monitoring analysis

Big difference between weighted and unweighted indexes

1

10

100

1992 1994 1996 1998 2000 2002 2004 2006

WeightedUnweighted

Page 21: Swaay butterfly monitoring analysis

The trend in the dunes is different from the trend on the heathlands

distribution

transects

1

10

100

1000

1990 1993 1996 1999 2002 2005

Heathland Coastal dunes

Page 22: Swaay butterfly monitoring analysis

From transects to European indicator

• Location of the transects • Quality of the observer • Quality of the observations • Validation of the observations • Calculating trends • Building indicators

Page 23: Swaay butterfly monitoring analysis

Grassland Butterfly Indicator: main habitat for European butterflies

• For 57% of the species, grasslands are their main habitat.

Grassland; 280

Woodland and scrub; 153

Heath, bog and fen; 25

others; 31

Page 24: Swaay butterfly monitoring analysis

17 species make the indicator

• 7 widespread species: Ochlodes sylvanus, Anthocharis cardamines, Lycaena phlaeas, Polyommatus icarus, Lasiommata megera, Coenonympha pamphilus Maniola jurtina

• 10 specialist species: Erynnis tages, Thymelicus acteon, Spialia sertorius, Cupido minimus, Maculinea arion, Maculinea nausithous, Polyommatus bellargus, Cyaniris semiargus, Polyommatus coridon Euphydryas aurinia

Page 25: Swaay butterfly monitoring analysis

From national trends to a European trend

0

25

50

75

100

125

150

175

1990 1994 1998 2002 2006 2010

Inde

x (fir

st y

ear=

100)

FranceThe NetherlandsSpain - CataloniaUnited Kingdom

0

20

40

60

80

100

120

1990 1994 1998 2002 2006 2010

Inde

x (19

90=1

00)

+ 9 other countries

Page 26: Swaay butterfly monitoring analysis

European species trends

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20

40

60

80

100

120

1990 1994 1998 2002 2006 2010

Inde

x (19

90=1

00)

0

20

40

60

80

100

120

140

160

1990 1994 1998 2002 2006 2010

Inde

x (19

90=1

00)

0

50

100

150

200

250

1990 1994 1998 2002 2006 2010

Inde

x (19

90=1

00)

Page 27: Swaay butterfly monitoring analysis

European trends

Species Trend in Europe Trend in EU Phengaris nausithous decline decline Erynnis tages decline decline Lasiommata megera decline decline Lycaena phlaeas decline decline Thymelicus acteon decline decline Ochlodes sylvanus decline decline Coenonympha pamphilus decline decline Cupido minimus decline decline Anthocharis cardamines decline stable Polyommatus icarus decline stable Maniola jurtina stable stable Polyommatus coridon stable stable Cyaniris semiargus uncertain stable Polyommatus bellargus uncertain uncertain Spialia sertorius uncertain uncertain Euphydryas aurinia uncertain uncertain Phengaris arion uncertain uncertain

Page 28: Swaay butterfly monitoring analysis

European Grassland Butterfly Indicator

0

20

40

60

80

100

120

140

1990 1994 1998 2002 2006 2010

Butterfly Conservation Europe / Statistics Netherlands

Page 29: Swaay butterfly monitoring analysis

Main drivers 1. Intensification

Page 30: Swaay butterfly monitoring analysis

Main drivers 2. Abandonment

Page 31: Swaay butterfly monitoring analysis
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Relationships between butterflies and environmental indicators

• Plants: Ellenberg values • Like plants some species have a preference for rich or

wet situations, others for poor or dry places

• Butterfly monitoring gave us info on the presence of butterflies

• We made vegetation surveys at transects and calculated the average Ellenberg value for Nutrient, acidity and moisture.

Page 34: Swaay butterfly monitoring analysis

Field data of occurrence of a species vs soil pH

Page 35: Swaay butterfly monitoring analysis

Logistic regression: sigmoid relationship

Page 36: Swaay butterfly monitoring analysis

Logistic regression: gaussian relationship

Page 37: Swaay butterfly monitoring analysis

0

10

20

30

40

50

60

0 1 2 3 4 5 6 7 8 9

Pro

ba

bil

ity

of

occ

urr

en

ce (%

)

Acidity-value (Ellenberg scale)

Pmax=37%

Tolerance=2.3

Optimum=5.0

Response curve of Araschnia levana for Ellenberg’s acidity-value, showing the Optimum (U), the maximum probability of occurrence (Pmax) and the Tolerance (T).

Page 38: Swaay butterfly monitoring analysis

0

20

40

60

80

0 2 4 6 8 10

Pro

b/Fr

eq o

f occ

urre

nce

(%)

Nutrient-value (Ellenberg scale)

(a) observed

expected

0

20

40

60

80

0 2 4 6 8 10P

rob/

Freq

of o

ccur

renc

e (%

) Nutrient-value (Ellenberg scale)

(b) observed

expected

Two examples of response curves of butterflies on Ellenberg’s nutrient value, showing the calculated logistic regression model (expected) and the observed frequency of the species in the relevés falling in nutrient value classes with a width of 0.25: (a) the unimodal (Gaussian) response of Thymelicus lineola and (b) the sigmoidal response of Ochlodes sylvanus.

Page 39: Swaay butterfly monitoring analysis

0

20

40

60

80

100

0 5 10

Prob

abili

ty o

f occ

urre

nce

(%)

Nutrient-value (Ellenberg-scale)

(a)

M. alconA. levanaC. seleneP. icarusP. rapae

Page 40: Swaay butterfly monitoring analysis

0

20

40

60

0 5 10

Prob

abili

ty o

f occ

urre

nce

(%)

Acidity-value (Ellenberg-scale)

(b)

C. tulliaI. ioE. tagesA. agestisC. pamphilus

Page 41: Swaay butterfly monitoring analysis

0

20

40

60

0 5 10

Prob

abili

ty o

f occ

urre

nce

(%)

Moisture-value (Ellenberg-scale)

(c)

V. optilete

M. alcon

E. tages

I. lathonia

L. megera

Page 42: Swaay butterfly monitoring analysis

Use butterfly monitoring results for site information

0

1

2

3

4

5

6

7

8

1990 1995 2000 2005 2010

Moi

stur

e / N

itrog

en v

alue

Moisture index

Nitrogen index

Luttenbergerven

Page 43: Swaay butterfly monitoring analysis

Multiple relationships

• Give the relationship between the three indicators • When more than one is significant, we get a multi-

dimensional plane or surface • For a site it can give an insight in the effects of a

changing environment on butterflies

Page 44: Swaay butterfly monitoring analysis

Calculate national annual nitrogen index for butterflies

5.7

5.8

5.9

6

6.1

6.2

6.3

6.4

6.5

1990 1995 2000 2005 2010

CN

I

Page 45: Swaay butterfly monitoring analysis

Calculate national annual nitrogen index for butterflies

y = 0.0131x - 20.205

5.7

5.8

5.9

6

6.1

6.2

6.3

6.4

6.5

1990 1995 2000 2005 2010

CN

I

Page 46: Swaay butterfly monitoring analysis

De Vlinderstichting Dutch Butterfly Conservation www.vlinderstichting.nl Statistics Netherlands www.cbs.nl