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Fauna monitoring in urban
forests of Lombardy
Emilio Padoa-Schioppa
University of Milano-Bicocca
Why monitoring?
«Conoscere per deliberare» (Luigi Einaudi) –
The knowledge is the starting point for any
decision
Biodiversity survey
We used birds as indicators of biodiversity
because:
• Ecological chains
• Linkage to environment
• Easy to contact
• Quantitave data
• Good knowledge of autoecology of
species
• Flag species for many people
Methodology
• Bird point count – 10 min. / unlimited
distance / 2 times during breeding season
Birds
Nome italiano Nome scientifico Nome Inglese
Airone cenerino Ardea cinerea Grey Heron
Fagiano Phasianus colchicus Pheasant
Colombaccio Columba palumbus Woodpigeon
Rondone Apus apus Common Swift
Picchio verde Picus viridis Green Woodpecker
Picchio rosso maggiore Dendrocopus major Great Spotted Woodpecker
Rondine Hirundo rustica Swallow
Pettirosso Erithacus rubecula Robin
Usignolo Luscinia megarhynchos Nightingale
Merlo Turdus merula Blackbird
Capinera Sylvia atricapilla Blackcap
Pigliamosche Muscicapa striata Spotted Flycatcher
Codibugnolo Aegithalos caudatus Long-tailed Tit
Cinciarella Parus caeruleus Blue Tit
Cinciallegra Parus major Great Tit
Picchio muratore Sitta europaea Nuthatch
Gazza Pica pica Magpie
Taccola Corvus monedula Jackdaw
Cornacchia grigia* Corvus (corone) corone Carrion Crow
Storno Sturnus vulgaris Starling
Fringuello Fringilla coelebs Chaffinch
Cardellino Carduelis carduelis Goldfinch
Birds
0
2
4
6
8
10
N°ofspecies
Point count
Species turn-over
S2
Common species
S1
Birds
0 2 4 6 8 10 12 14 16
Grey Heron
Pheasant
Spotted Flycatcher
Nuthatch
Jackdaw
Common Swift
Swallow
Robin
Blue Tit
Magpie
Goldfinch
Green Woodpecker
Long-tailed Tit
Starling
Woodpigeon
Great Tit
Nightingale
Carrion Crow
Great Spotted Woodpecker
Chaffinch
Blackcap
Blackbird
Birds
Insects: butterflies
and carabids
Data:
29/05/20
12
10/07/2
012
01/08/201
2 23/08/2012
14/09/201
2
Species 1 2 3 4 5
Argynnis paphia (Linné, 1758) x
Celastrina argiolus (Linné, 1758) x x
Colias crocea (Geoffroy, 1785) x x
Vanessa atalanta (Linné, 1758) x
Aricia agestis ([Denis & Schiffermüller],
1775) x x x
Cupido argiades (Pallas, 1771) x x x x
Iphiclides podalirius (Linné, 1758) x
Issoria lathonia (Linné, 1758) x
Melitaea athalia (Rottemburg, 1775) x x
Ochlodes venatus (Bremer & Grey, 1853) x
Papilio machaon Linné, 1758 x
Pararge aegeria (Linné, 1758) x x x x x
Pieris brassicae (Linné, 1758) x x
Pieris napi (Linné, 1758) x x x x
Pieris rapae (Linné, 1758) x
Polygonia c-album (Linné, 1758) x x x x
Polyommatus icarus (Rottemburg, 1775) x x x
Satyrium w-album (Knoch, 1782) x
Insects: butterflies and carabids
0
5
10
15
20
25
30
N° specie
N°specie
Carabidi
Foresta Carpaneta
Parco nord 1
Parco nord 2
Conclusions
• Sampling protocols allow to get a good knowledge of
biodiversity
• Birds (species and abundance) appear to be linked to forest
structure
• Butterflies are linked also to landscape contest (more species
in open areas)
Management & Biodiversity
How management decision may
influence biodiversity?
Biodiversity conservation
in urban parks
Landscape
EcosystemCommunity
Forest structure
Tree diversity
… … …
Area of park
Forest coverage
… … …
Landscape heterogeneity
Distance from center
… … …
Large parks of
Milano suburbs
Parks of Bari
Parks of
Milano city
Cluster analysis
MI 2
MI 9
MI 4
MI 12
MI 10
MI 7
MI 13
MI 6
MI 11
MI 5
BA 1
BA 2
BA 3
MI 1
MI 3
MI 8
Dendrogram using Average Linkage (Between Groups)
Rescaled Distance Cluster Combine
0 5 10 15 20 25
Sanesi et al., AUF, 2009
y = 0,0027x + 6,3432
R2
= 0,5738
0
10
20
30
40
0 2000 4000 6000 8000 10000
Distanza dal centro città (m)
n°dispecie
y = 5,4094Ln(x) + 0,2575
R
2
= 0,697
0
5
10
15
20
25
30
35
40
0 100 200 300 400 500 600 700
Area (ha)
n°specie
y = 0,3943x + 9,3607
R2
= 0,7802
0
10
20
30
40
50
0 20 40 60 80 100
Copertura arborea (ha)
n°dispecie
Biodiversity and forests management
Sanesi et al., AUF, 2009
Forest structure
?
We selected 4 targets specie
– Turdus merula
– Fringilla coelebs
– Parus major
– Serinus serinus
From literature (Massa et al., 2004;
Fornasari 2006) linked to forest structure
but present also in urban envirnoment
Forest structure and bird abundance
DBH – min / 1° quartile / median / 3° quartile / max
Abundance of target species
Forest structure and
bird abundanceTest Statistics(a)
D min Blue tit
Mann-Whitney U 335,000
Z -,459
Asymp. Sig. (2-tailed) ,646
a Grouping Variable: CLASSE 5
Test Statistics(a)
Diametro minimo Blue tit
Mann-Whitney U 404,500
Z -,286
Asymp. Sig. (2-tailed) ,775
a Grouping Variable: CLASSE 10
Test Statistics(a)
1° quartile Blue tit
Mann-Whitney U 287,000
Z -1,771
Asymp. Sig. (2-tailed) ,077
a Grouping Variable: CLASSE 10
Test Statistics(a)
1° quartile Blue tit
Mann-Whitney U 470,500
Z -1,024
Asymp. Sig. (2-tailed) ,306
a Grouping Variable: CLASSE 20
Test Statistics(a)
mediane Blue tit
Mann-Whitney U 466,000
Z -1,598
Asymp. Sig. (2-tailed) ,110
a Grouping Variable: CLASSE 20
Test Statistics(a)
mediane Blue tit
Mann-Whitney U 371,000
Z -1,020
Asymp. Sig. (2-tailed) ,308
a Grouping Variable: CLASSE 30
Test Statistics(a)
3° quartile Blue tit
Mann-Whitney U 485,000
Z -1,040
Asymp. Sig. (2-tailed) ,298
a Grouping Variable: CLASSE 30
Test Statistics(a)
3° quartile Blue tit
Mann-Whitney U 328,500
Z -1,148
Asymp. Sig. (2-tailed) ,251
a Grouping Variable: CLASSE 40
Test Statistics(a)
Diametro max Blue tit
Mann-Whitney U 489,000
Z -1,301
Asymp. Sig. (2-tailed) ,193
a Grouping Variable: CLASSE 60
Test Statistics(a)
Diametro max Blue tit
Mann-Whitney U 292,000
Z -1,937
Asymp. Sig. (2-tailed) ,053
a Grouping Variable: CLASSE 80
Sanesi et al., AUF, 2009
Blue tit & forest structure
Blue tit
y = 5,8371e0,0261x
R2
= 0,9995
y = 3,6159e0,0236x
R2
= 0,9925
0
20
40
60
80
100
0 25 50 75 100
Tree n°
DBH
Minimum
Optimal
Sanesi et al., AUF, 2009

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Padoa schioppa fauna monitoring

  • 1. Fauna monitoring in urban forests of Lombardy Emilio Padoa-Schioppa University of Milano-Bicocca
  • 2. Why monitoring? «Conoscere per deliberare» (Luigi Einaudi) – The knowledge is the starting point for any decision
  • 3. Biodiversity survey We used birds as indicators of biodiversity because: • Ecological chains • Linkage to environment • Easy to contact • Quantitave data • Good knowledge of autoecology of species • Flag species for many people Methodology • Bird point count – 10 min. / unlimited distance / 2 times during breeding season
  • 4. Birds Nome italiano Nome scientifico Nome Inglese Airone cenerino Ardea cinerea Grey Heron Fagiano Phasianus colchicus Pheasant Colombaccio Columba palumbus Woodpigeon Rondone Apus apus Common Swift Picchio verde Picus viridis Green Woodpecker Picchio rosso maggiore Dendrocopus major Great Spotted Woodpecker Rondine Hirundo rustica Swallow Pettirosso Erithacus rubecula Robin Usignolo Luscinia megarhynchos Nightingale Merlo Turdus merula Blackbird Capinera Sylvia atricapilla Blackcap Pigliamosche Muscicapa striata Spotted Flycatcher Codibugnolo Aegithalos caudatus Long-tailed Tit Cinciarella Parus caeruleus Blue Tit Cinciallegra Parus major Great Tit Picchio muratore Sitta europaea Nuthatch Gazza Pica pica Magpie Taccola Corvus monedula Jackdaw Cornacchia grigia* Corvus (corone) corone Carrion Crow Storno Sturnus vulgaris Starling Fringuello Fringilla coelebs Chaffinch Cardellino Carduelis carduelis Goldfinch
  • 6. Birds 0 2 4 6 8 10 12 14 16 Grey Heron Pheasant Spotted Flycatcher Nuthatch Jackdaw Common Swift Swallow Robin Blue Tit Magpie Goldfinch Green Woodpecker Long-tailed Tit Starling Woodpigeon Great Tit Nightingale Carrion Crow Great Spotted Woodpecker Chaffinch Blackcap Blackbird
  • 8. Insects: butterflies and carabids Data: 29/05/20 12 10/07/2 012 01/08/201 2 23/08/2012 14/09/201 2 Species 1 2 3 4 5 Argynnis paphia (Linné, 1758) x Celastrina argiolus (Linné, 1758) x x Colias crocea (Geoffroy, 1785) x x Vanessa atalanta (Linné, 1758) x Aricia agestis ([Denis & Schiffermüller], 1775) x x x Cupido argiades (Pallas, 1771) x x x x Iphiclides podalirius (Linné, 1758) x Issoria lathonia (Linné, 1758) x Melitaea athalia (Rottemburg, 1775) x x Ochlodes venatus (Bremer & Grey, 1853) x Papilio machaon Linné, 1758 x Pararge aegeria (Linné, 1758) x x x x x Pieris brassicae (Linné, 1758) x x Pieris napi (Linné, 1758) x x x x Pieris rapae (Linné, 1758) x Polygonia c-album (Linné, 1758) x x x x Polyommatus icarus (Rottemburg, 1775) x x x Satyrium w-album (Knoch, 1782) x
  • 9. Insects: butterflies and carabids 0 5 10 15 20 25 30 N° specie N°specie Carabidi Foresta Carpaneta Parco nord 1 Parco nord 2
  • 10. Conclusions • Sampling protocols allow to get a good knowledge of biodiversity • Birds (species and abundance) appear to be linked to forest structure • Butterflies are linked also to landscape contest (more species in open areas)
  • 11. Management & Biodiversity How management decision may influence biodiversity? Biodiversity conservation in urban parks Landscape EcosystemCommunity Forest structure Tree diversity … … … Area of park Forest coverage … … … Landscape heterogeneity Distance from center … … …
  • 12. Large parks of Milano suburbs Parks of Bari Parks of Milano city Cluster analysis MI 2 MI 9 MI 4 MI 12 MI 10 MI 7 MI 13 MI 6 MI 11 MI 5 BA 1 BA 2 BA 3 MI 1 MI 3 MI 8 Dendrogram using Average Linkage (Between Groups) Rescaled Distance Cluster Combine 0 5 10 15 20 25 Sanesi et al., AUF, 2009
  • 13. y = 0,0027x + 6,3432 R2 = 0,5738 0 10 20 30 40 0 2000 4000 6000 8000 10000 Distanza dal centro città (m) n°dispecie y = 5,4094Ln(x) + 0,2575 R 2 = 0,697 0 5 10 15 20 25 30 35 40 0 100 200 300 400 500 600 700 Area (ha) n°specie y = 0,3943x + 9,3607 R2 = 0,7802 0 10 20 30 40 50 0 20 40 60 80 100 Copertura arborea (ha) n°dispecie Biodiversity and forests management Sanesi et al., AUF, 2009
  • 14. Forest structure ? We selected 4 targets specie – Turdus merula – Fringilla coelebs – Parus major – Serinus serinus From literature (Massa et al., 2004; Fornasari 2006) linked to forest structure but present also in urban envirnoment
  • 15. Forest structure and bird abundance DBH – min / 1° quartile / median / 3° quartile / max Abundance of target species
  • 16. Forest structure and bird abundanceTest Statistics(a) D min Blue tit Mann-Whitney U 335,000 Z -,459 Asymp. Sig. (2-tailed) ,646 a Grouping Variable: CLASSE 5 Test Statistics(a) Diametro minimo Blue tit Mann-Whitney U 404,500 Z -,286 Asymp. Sig. (2-tailed) ,775 a Grouping Variable: CLASSE 10 Test Statistics(a) 1° quartile Blue tit Mann-Whitney U 287,000 Z -1,771 Asymp. Sig. (2-tailed) ,077 a Grouping Variable: CLASSE 10 Test Statistics(a) 1° quartile Blue tit Mann-Whitney U 470,500 Z -1,024 Asymp. Sig. (2-tailed) ,306 a Grouping Variable: CLASSE 20 Test Statistics(a) mediane Blue tit Mann-Whitney U 466,000 Z -1,598 Asymp. Sig. (2-tailed) ,110 a Grouping Variable: CLASSE 20 Test Statistics(a) mediane Blue tit Mann-Whitney U 371,000 Z -1,020 Asymp. Sig. (2-tailed) ,308 a Grouping Variable: CLASSE 30 Test Statistics(a) 3° quartile Blue tit Mann-Whitney U 485,000 Z -1,040 Asymp. Sig. (2-tailed) ,298 a Grouping Variable: CLASSE 30 Test Statistics(a) 3° quartile Blue tit Mann-Whitney U 328,500 Z -1,148 Asymp. Sig. (2-tailed) ,251 a Grouping Variable: CLASSE 40 Test Statistics(a) Diametro max Blue tit Mann-Whitney U 489,000 Z -1,301 Asymp. Sig. (2-tailed) ,193 a Grouping Variable: CLASSE 60 Test Statistics(a) Diametro max Blue tit Mann-Whitney U 292,000 Z -1,937 Asymp. Sig. (2-tailed) ,053 a Grouping Variable: CLASSE 80 Sanesi et al., AUF, 2009
  • 17. Blue tit & forest structure Blue tit y = 5,8371e0,0261x R2 = 0,9995 y = 3,6159e0,0236x R2 = 0,9925 0 20 40 60 80 100 0 25 50 75 100 Tree n° DBH Minimum Optimal Sanesi et al., AUF, 2009