Assessing the effects of the spatial components on species diversity in a network of protected areas represents an important step for assessing its conservation ''capacity''. A clear evaluation on how a-, b-, and g-diversity are partitioned among and within spatial scales can help to drive manager decisions and provide method for monitoring species diversity. Moving from these concepts, a probabilistic sample of plant species composition was here applied for quantifying plant species diversity within the Sites of Community Importance (SCIs) of the Natura 2000 network in the Siena Province. All analyses were performed separately for all species and those species defined as ''focal'' (included in regional, national or continental ''red'' lists). The results indicated that species richness of the SCIs differed from one location to another one independently from the sampling efforts. Diversity partitioning indicated that most of the flora diversity within the network was given by larger-scale bdiversity, i.e. the differences in species composition among SCIs. b-diversity was then decomposed in two components: bArea (due to the differences in area among SCIs) and bReplacement (due to the compositional differences across SCIs). bArea was particularly important for all species, while bReplacement was the most important factor for focal species. The consequent implications for monitoring and nature conservation strategies are discussed.

Quantifying plant species diversity in a Natura 2000 network: Old ideas and new proposals / CHIARUCCI A.; BACARO G.; ROCCHINI D.. - In: BIOLOGICAL CONSERVATION. - ISSN 0006-3207. - STAMPA. - 141:10(2008), pp. 2608-2618. [10.1016/j.biocon.2008.07.024]

Quantifying plant species diversity in a Natura 2000 network: Old ideas and new proposals

CHIARUCCI, ALESSANDRO;ROCCHINI D.
2008

Abstract

Assessing the effects of the spatial components on species diversity in a network of protected areas represents an important step for assessing its conservation ''capacity''. A clear evaluation on how a-, b-, and g-diversity are partitioned among and within spatial scales can help to drive manager decisions and provide method for monitoring species diversity. Moving from these concepts, a probabilistic sample of plant species composition was here applied for quantifying plant species diversity within the Sites of Community Importance (SCIs) of the Natura 2000 network in the Siena Province. All analyses were performed separately for all species and those species defined as ''focal'' (included in regional, national or continental ''red'' lists). The results indicated that species richness of the SCIs differed from one location to another one independently from the sampling efforts. Diversity partitioning indicated that most of the flora diversity within the network was given by larger-scale bdiversity, i.e. the differences in species composition among SCIs. b-diversity was then decomposed in two components: bArea (due to the differences in area among SCIs) and bReplacement (due to the compositional differences across SCIs). bArea was particularly important for all species, while bReplacement was the most important factor for focal species. The consequent implications for monitoring and nature conservation strategies are discussed.
2008
Quantifying plant species diversity in a Natura 2000 network: Old ideas and new proposals / CHIARUCCI A.; BACARO G.; ROCCHINI D.. - In: BIOLOGICAL CONSERVATION. - ISSN 0006-3207. - STAMPA. - 141:10(2008), pp. 2608-2618. [10.1016/j.biocon.2008.07.024]
CHIARUCCI A.; BACARO G.; ROCCHINI D.
File in questo prodotto:
Eventuali allegati, non sono esposti

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/382540
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 76
  • ???jsp.display-item.citation.isi??? 74
social impact