This document summarizes research on monitoring biodiversity in urban forests in Lombardy, Italy. Birds and insects were used as indicators of biodiversity. Over 20 species of birds were recorded during point counts in forests. Butterfly and beetle species were also surveyed across forest sites. Analysis found links between biodiversity and forest structure, with certain bird species more abundant where there was greater tree diameter variability. The results can inform forest management decisions to help conserve urban biodiversity.

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

5. Birds
0
2
4
6
8
10
N°ofspecies
Point count
Species turn-over
S2
Common species
S1

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

7. Birds

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