Swaay butterfly monitoring analysis

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Transcript of 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)

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

Products

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1992 1994 1996 1998 2000 2002 2004

Woodland generalistsWoodland specialists

Species trends

Indicators

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1992 1994 1996 1998 2000 2002 2004 2006 2008

GeelsprietdikkopjeThymelicus sylvestris

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

The start

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

• 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

Butterfly Monitoring Spatial coverage • New countries join in

every year • Most of them done

every year

Butterfly Monitoring Temporal coverage

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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

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

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)

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

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

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’.

Weighting by Dutch physical geographic region and main habitat type

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

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

Distribution of the transects over the strata

Dunes - mainland

Dunes - WaddenseaHeathland - north

Heathland - centre

Heathland - southdistribution

Big difference between weighted and unweighted indexes

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WeightedUnweighted

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

distribution

transects

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Heathland Coastal dunes

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

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

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

From national trends to a European trend

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FranceThe NetherlandsSpain - CataloniaUnited Kingdom

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+ 9 other countries

European species trends

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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

European Grassland Butterfly Indicator

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Butterfly Conservation Europe / Statistics Netherlands

Main drivers 1. Intensification

Main drivers 2. Abandonment

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.

Field data of occurrence of a species vs soil pH

Logistic regression: sigmoid relationship

Logistic regression: gaussian relationship

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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).

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Nutrient-value (Ellenberg scale)

(a) observed

expected

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) Nutrient-value (Ellenberg scale)

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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.

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Nutrient-value (Ellenberg-scale)

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M. alconA. levanaC. seleneP. icarusP. rapae

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Acidity-value (Ellenberg-scale)

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C. tulliaI. ioE. tagesA. agestisC. pamphilus

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Moisture-value (Ellenberg-scale)

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V. optilete

M. alcon

E. tages

I. lathonia

L. megera

Use butterfly monitoring results for site information

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Moi

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Moisture index

Nitrogen index

Luttenbergerven

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

Calculate national annual nitrogen index for butterflies

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CN

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Calculate national annual nitrogen index for butterflies

y = 0.0131x - 20.205

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