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The role of protected areas in preserving habitat and functional connectivity for mobile flying vertebrates: the common noctule bat (Nyctalus noctula) in Tuscany (Italy) as a case study

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Abstract

Preserving species within protected areas (PAs) does not guarantee adequate levels of protection if not coupled with conservation of functional connectivity for a target species. We propose an analytical framework to assess the effectiveness of PAs in preserving habitat and functional connectivity for mobile vertebrates. We implemented it in central Italy by using as a case study a bat species (common noctule, Nyctalus noctula) to: (i) determine suitable areas by means of Species Distribution Models (SDMs); (ii) identify potential commuting corridors through a functional connectivity analysis; (iii) develop a new tool to rank corridors according to their functional irreplaceability; (iv) implement a gap analysis on both suitable areas and functional corridors; and (v) propose management recommendations for the conservation of N. noctula. The SDM output and a set of proxies of commuting routes were used to build a resistance layer for the connectivity analysis. The resulting functional corridors were ranked according to their isolation (distance to other corridors and to suitable areas) to obtain an irreplaceability index, with isolated corridors scoring high values. The PA effectiveness assessed by overlapping the PA map with the SDM and the ranked functional corridors highlighted that PAs cover just a small portion of suitable sites (20.3%) and functional corridors for the species (20.8%). The irreplaceability index allowed us to identify those areas inside and outside the PAs that critical for persistence of the species in question require immediate protection regimes. The approach we present could be easily extended to other taxa and offers sound insight on how to promote the conservation at landscape scale.

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Acknowledgements

We thank NEMO s.r.l. for providing the maps of protected areas. Thanks also go to Erin Landguth for her support in the UNICOR procedures.

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Author information

Author notes

  1. L. Ducci and F. Roscioni have contributed equally to the manuscript.

Authors and Affiliations

  1. Dipartimento di Biologia, Università degli Studi di Firenze, Via Madonna del Piano 6, 50019, Sesto Fiorentino, FI, Italy

    L. Ducci & G. Santini

  2. Museo di Storia Naturale, Università degli Studi di Firenze, Via Romana 17, 50125, Florence, Italy

    L. Ducci & P. Agnelli

  3. Envix-Lab, Dipartimento di Bioscienze e Territorio, Università degli Studi del Molise, Contrada Fonte Lappone, 86090, Pesche, IS, Italy

    F. Roscioni, M. L. Carranza, L. Frate, A. Loy & M. Di Febbraro

  4. Ecomodel Società Cooperativa, Via Tiberina 149, 00188, Rome, Italy

    F. Roscioni & M. Di Febbraro

  5. Wildlife Research Unit, Laboratorio di Ecologia Applicata, Dipartimento di Agraria, Università degli Studi di Napoli Federico II, Via Università 100, 80055, Portici, NA, Italy

    D. Russo

  6. School of Biological Sciences, University of Bristol, Woodland Road, BS8 1UG, Bristol, UK

    D. Russo

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Correspondence to M. L. Carranza.

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Appendices

Appendix 1

Environmental variables and maps used for modelling the distribution of N. Noctula in the Tuscany region: (a) environmental variables, (b) reclassification scheme for Corine Land Cover, (c) reclassified Corine Land Cover map.


(a) Environmental variables used in the Species Distribution Model for N. Noctula. DEM: Digital Elevation Model. CLC: Corine Land Cover.

Variables

Code

Source of maps and scale

Elevation (m)

DEM

DEM: cell size 100 m

Year 2005 MATTM Geoportale Nazionale

Hidrography

Hydro

Hydrographic map: scale: 1:100.000

Year 2008 MATTM-Geoportale Nazionale

Cover types

ReclCLC

Corine Land Cover map: scale: 1:100.000 year 2006 EEA CLC expanded to a IV level of detail developed for Italy (MATTM- Geoportale Nazionale)


(b) Reclassification scheme for Corine Land Cover.

CLC original codes

CLC names

New classes

New names

1.1.1

Continuous urban fabric

100

Urban

1.1.2

Discontinuous urban fabric

100

Urban

1.2.1

Industrial or commercial unit

100

Urban

1.2.2

Road and rail networks and associated land

100

Urban

1.2.3

Port areas

100

Urban

1.2.4

Airports

100

Urban

1.3.1

Mineral extraction sites

131

Mineral extraction sites

1.3.2

Dump sites

100

Urban

1.3.3

Construction sites

100

Urban

1.4.1

Green urban areas

100

Urban

1.4.2

Sport and leisure facilities

100

Urban

2.1.1.

Non-irrigated arable land

210

Cultivation

2.1.3

Rice fields

210

Cultivation

2.2.1

Vineyards

220

Orchard

2.2.2

Fruit trees and berry plantation

220

Orchard

2.2.3

Olive groves

220

Orchard

2.3.1

Pastures

230

Pastures

2.4.1

Annual crops associated with permanent crops

240

Heterogeneous agricultural areas

2.4.2

Complex cultivation pattern

240

Heterogeneous agricultural areas

2.4.3

Land principally occupied by agriculture, with significant areas of natural vegetation

240

Heterogeneous agricultural areas

2.4.4

Agro-forestry area

240

Heterogeneous agricultural areas

3.1.1

Broad-leaved forests

310

Forests

3.1.1.1

Holm-oak and cork-oak forests

310

Forests

3.1.1.2

Decidous oak forests

310

Forests

3.1.1.3

Mesophillous broad-leaved forests

310

Forests

3.1.1.4

Chestnut forests

310

Forests

3.1.1.5

Beech forests

310

Forests

3.1.1.6

Igrophyllous forests

3.1.1.6

Riparian forests

3.1.1.7

Exotic broad-leaved forests

310

Forests

3.1.2

Coniferous forests

312

Coniferous

3.1.2.1

Mediterranean pine forests

312

Coniferous

3.1.2.2

Mountain and oromediterranean pine forests

312

Coniferous

3.1.2.3

Spruce forests

312

Coniferous

3.1.2.5

Exotic coniferous forests

312

Coniferous

3.1.3

Mixed forests

 

Mixed forests

3.1.3.1

Broad lived dominated forests

313

Mixed forests

3.1.3.2

Coniferous dominated forests

313

Mixed forests

3.2.1

Natural grassland

321

Steppe

3.2.1.1.

Continuous grassland

321

Steppe

3.2.1.2

Discontinuous grassland

321

Steppe

3.2.3

Sclerophyllous vegetation

323

Scrubs

3.2.3.1

Tall maquis

323

Scrubs

3.2.3.2

Low maquis and garrigue

323

Scrubs

3.2.4

Transitional woodland-shrub

323

Scrubs

3.3.1

Beaches dune and sands

330

Bare ground

3.3.2

Bare rocks

330

Bare ground

3.3.3

Sparsely vegetated area

330

Bare ground

4.1.1

Inland marshes

410

Water

4.2.1

Salt marshes

510

Salt Water

4.2.2

Salines

510

Salt Water

5.1.1

Water courses

410

Water

5.1.2

Water bodies

410

Water

5.2.1

Coastal lagoons

510

Salt Water


(c) Reclassified Corine Land Cover map of Tuscany region (ReclCLC).

figure a

Appendix 2

figure b

Resistance surface for N. noctula in Tuscany region (Central Italy). Low resistance refers to the suitable areas for the species, medium resistance to areas that being external to suitable habitats contain elements that allow bat movement as high slopes, forest edges and watercourses. High resistance indicates unsuitable areas with no connecting elements for the species.

Appendix 3

Variables importance and response curves for Nyctalus noctula in Tuscany region (central Italy) as identified by MaxEnt analysis. (a) Jacknife of regularized training gain to highlight the variable importance; (b) Response curves.

figure c

The environmental variable with the highest gain is ReclCLC, which therefore appears to have the most useful information by itself. In fact this variable is also the one that decreases most the gain when it is omitted.

figure d

Response curve of Nyctalus noctula to DEM. The curve shows the mean response of the 50 replicate Maxent runs (red) and the mean standard deviation (blue).

figure e

Response curve of Nyctalus noctula to Hydro. The curve shows the mean response of the 50 replicate Maxent runs (red) and the mean standard deviation (blue).

figure f

Response of Nyctalus noctula to ReclCLC. The response of this variable is expressed by a bar plot as it is categorical. CLC codes: 100—urban; 131—mineral extraction sites; 210—cultivation; 220—orchards; 230—pastures; 240—heterogeneous agricultural areas; 310—broad leaved forests; 3116—riparian forests; 312—coniferous; 313—mixed forests; 321—steppe; 323—scrubs; 330—bare ground; 410—water; 510—salt water.

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Ducci, L., Roscioni, F., Carranza, M.L. et al. The role of protected areas in preserving habitat and functional connectivity for mobile flying vertebrates: the common noctule bat (Nyctalus noctula) in Tuscany (Italy) as a case study. Biodivers Conserv 28, 1569–1592 (2019). https://doi.org/10.1007/s10531-019-01744-5

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